Overview :Use the spoiler-free clues to work through today’s four Quordle grids.Check the starting letters and repeated-letter clue to narrow down the possible answers.Scroll further only when you’re ready to reveal all four solutions.Quordle players looking for help with today’s puzzle can use the clues below before revealing the four five-letter answers. The August 12 puzzle brings together words associated with strong emotion, groups of people, the human body, and seawater moving onto the shore.Unlike traditional word games, Quordle requires players to solve four words simultaneously. Each guess is applied to all four grids, so identifying common letters and their positions can help narrow down multiple answers at once.Quordle Hints for August 12Players who are stuck can use the following clues without immediately giving away the answers.Word 1 (Top Left): An adverb describing something done in a passionate, excited or angry way, as in ‘_____ anticipated.’Word 2 (Top Right): A large group of people.Word 3 (Bottom Left): The organ that keeps us ticking along.Word 4 (Bottom Right): The rush of seawater toward the beach after a wave breaks.There is another clue for players who need an additional push: one of today’s words contains a pair of repeated letters.The four answers begin with H, C, H and S, respectively.One Last Clue Before AnswersThe starting letters should make the possibilities easier to narrow down. Look for an H word describing something done with strong emotion, a C word meaning a large group of people, another H word connected to the body, and an S word describing seawater rushing onto the shore.If you want to solve the puzzle without spoilers, this is the point to stop reading.Quordle Answers for August 12Spoiler alert: The four answers to today’s Quordle are:HOTLYCROWDHEARTSWASHWhat do Today’s Quordle Answers Mean?HOTLY: Means in a passionate, intense, or emotional manner. It can describe something that is strongly anticipated, debated, or pursued.CROWD: Refers to a large number of people gathered together in one place.HEART: The muscular organ that pumps blood around the body and keeps the circulatory system working.SWASH: Describes the rush or surge of seawater up the beach after a wave breaks.How Difficult was Today’s Quordle?Today’s Quordle combines four familiar words with clues from very different contexts. HOTLY can be identified through its connection to passionate or intense action, while CROWD is a straightforward match for the large-group clue.HEART is likely to stand out once the body-related clue and starting letter are considered. SWASH may be the trickiest of the four, as it refers to the movement of seawater along the shore.The repeated-letter clue can also help confirm the correct solution. Players who solved all four without checking the answers have completed today’s challenge.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

India’s solar industry is seeing a different AI trend, with automation reducing routine work while raising salaries. In 2026, solar manufacturers are using AI systems to check products and identify factory problems.The technology reduces manual inspection work while creating demand for workers with AI and automation skills. Industry estimates show green energy salaries could rise 12% to 30% across experience levels this year. Entry-level salaries could increase 12% to 15%, while mid-level roles may gain 18% to 22%. Senior professionals could see increases between 25% and 30%, according to industry estimates.Solar factories now use AI-powered cameras to find defects during production. Predictive tools can also identify problems before they become larger production issues. Automated systems can even change some production settings after detecting problems during manufacturing. These changes reduce repetitive tasks while creating new roles that require greater technical expertise. Workers must monitor machines, review data, adjust systems, and refine AI models as conditions change. Vijay Menon, COO of Navitas Solar, said, “We'd encourage the industry to look at AI adoption in solar manufacturing not through the lens of jobs lost, but through the value and skill level of the jobs being created.”Menon also said the bigger challenge involves finding workers who can handle advanced manufacturing systems. The shortage highlights rising demand for people who understand manufacturing, AI, automation, and process controls. Companies investing in training could improve production quality while creating better-paid clean energy careers.India’s clean energy transition could generate more than 35 million green jobs by 2047. This growth could create around 1.6 million jobs every year across clean energy industries. Future roles may focus more on AI-powered machines, data, automation, and engineering skills.The solar industry shows how AI can change jobs rather than simply remove them. Routine work may decline, while skilled roles could offer stronger salaries and career opportunities.Also Read: India Faces Lower AI Job Disruption Risk: World BankJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

The FTSE 100 opened 7.39 points lower at 10,836.80 ahead of anticipated US inflation data, and as oil continues to rise amid tensions in the Middle East. Brent crude futures rose 0.67% to $89.51 per barrel. US West Texas Intermediate (WTI) advanced 0.72% to $83.80 per barrel. Sterling fell to $1.3511 on Tuesday from $1.3522 in the previous session. Against the euro, it fell to €1.1702 from €1.1708.Gainers & LosersOn the upside, Lion Finance Group climbed 1.66% to 12,840p. Rolls-Royce Holdings advanced 1.50% to 1,556p, while Endeavour Mining gained 1.46% to 4,244p. BAE Systems rose 1.44% to 2,262p, Babcock International Group added 1.30% to 1,206.50p, and Barratt Redrow increased 1.25% to 323.20p.On the downside, RELX fell 1.50% to 2,569p. Next declined 1.32% to 15,380p, while Reckitt Benckiser Group dropped 0.98% to 5,232p. AstraZeneca slipped 0.93% to 11,734p, London Stock Exchange Group lost 0.73% to 8,742p, and Spirax Group edged 0.62% lower to 7,180p.Trump Says U.S. has Total Control of Hormuz US President Donald Trump, speaking on Tuesday, reiterated US ‘total control’ over the Strait, saying "We have total control over the Strait of Hormuz right now... We own it," while warning Tehran of a ‘forceful’ response to any retaliation.Balfour Beatty Raises OutlookBalfour Beatty increased its earnings and cash flow targets. The group has seen the value of its order book jump by 17% to £22.9 billion in the six months to June, as its revenue increased by 8% to £5.6 billion. This revenue boost was driven by rising demand in US housebuilding and the UK’s power industry, the firm said. The group lifted its earnings targets from low single-digit to high double-digit growth and hiked the upper limit of its net cash forecast from £1.5 billion to £1.7 billion.Hill & Smith Raised Profit TargetHill & Smith has raised its profit targets for the year after a strong first half. The firm posted an 8% rise in revenue to $606.7 million following demand in US power grids and data center markets. It said it expects full-year profit to be ‘modestly ahead of previous expectations,’ after penciling in $212m previously. The group disposed of its lower-margin UK permanent steel road barrier business to reduce exposure to the weaknesses in the sector. Hill & Smith hiked its interim dividend to 25c per share, up 7%.Also Read: Stock Market Update: Nifty 50 Started Flat, Sensex Rose 109 pointsGlobal Market ViewIn the US, the S&P 500 lost 0.32%, dropping for a second day and closing at 7,728.20. The Nasdaq Composite fell 0.60% and the Dow Jones Industrial Average shed 184.13 points, or 0.34%.In Asia on Wednesday, Tokyo's Nikkei 225 fell 0.83% to 67,524.06, while China’s Shanghai Composite gained 0.32%. Hong Kong’s Hang Seng declined 0.97%, and South Korea’s Kospi edged higher by 3.68%. In India, both the Nifty 50 and the Sensex fell by 0.81% and 0.77%, respectively.

Ola Electric: Q1 FY27 Revenue: Revenue from operations reached Rs 455 crore, rising 72% sequentially but falling 45% year-on-year, showing mixed financial momentum overall.Ola Electric: Vehicle Deliveries: Ola Electric delivered 39,192 vehicles, nearly doubling quarterly deliveries as demand recovered following operational changes implemented during the previous fiscal year.Ola Electric: Order Growth: Orders surged to approximately 44,071 units from 22,522 previously, pointing toward stronger customer interest and improving demand momentum during Q1 FY27.Ola Electric: Market Share: Ola Electric’s market share recovered to 8.4% from 5.1%, outperforming broader electric two-wheeler market registration growth during the quarter.Ola Electric: Net Loss: Net loss narrowed to Rs 336 crore from Rs 500 crore sequentially, indicating meaningful improvement despite continued pressure on overall profitability.Ola Electric: Gross Margin: Consolidated gross margin stood at 30.5%, remaining resilient despite commodity pressures and highlighting improved economics across the electric vehicle business.Ola Electric: Operating Costs: Consolidated operating expenses declined 22% quarter-on-quarter to Rs 333 crore, reflecting the company’s continued focus on cost discipline and efficiency.Ola Electric: The Catch: Despite sequential improvement, revenue remained 45% below last year, while the company continued reporting substantial losses, limiting claims of recovery.Ola Electric: Overall Verdict: The quarter looked better operationally, but persistent losses and weaker annual revenue mean Ola’s turnaround remains unfinished and closely watched.Read More StoriesJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Solana’s stablecoin economy has expanded sharply over the past three years, strengthening the network’s position as a major settlement layer for crypto payments, decentralized finance and tokenized assets.According to Artemis data cited by @solana_sailor, stablecoin supply on Solana increased from roughly $1.5 billion three years ago to about $16.7 billion as of August 9, 2026. That represents an increase of more than 11 times, compared with roughly 2.5 times growth for the broader stablecoin market over the same period.The expansion has pushed Solana into third place globally for stablecoin supply, behind only Ethereum and Tron.USDC Dominates Solana’s Stablecoin MarketUSDC remains the largest stablecoin on Solana, accounting for approximately 75%-80% of supply and more than $10.5 billion in value, according to Artemis data.USDT, PayPal’s PYUSD and yield-bearing stablecoins such as Ondo’s USDY make up much of the remaining supply.Circle’s USDC presence has expanded alongside payment and settlement integrations, giving Solana deep liquidity for dollar-denominated transactions. The network’s low fees and high throughput make it particularly suited to stablecoin transfers where speed and transaction cost matter.Stablecoin Transfer Volume Tops $500 BillionThe growth is not limited to tokens sitting on-chain. According to Artemis, Solana processed more than $500 billion in stablecoin transfer volume during July 2026. Earlier in the year, February volume reached approximately $650 billion, briefly putting Solana ahead of Ethereum in monthly stablecoin transfer activity.The figures suggest Solana is increasingly being used as an active payment and settlement network rather than merely a place to hold digital dollars.Institutional Use Cases Continue to ExpandInstitutional adoption is also adding momentum. Western Union’s USDPT-backed Stablecard reportedly launched on Solana in August across 37 countries, supporting payments at approximately 175 million merchant locations.BlackRock has also expanded tokenized money-market products onto Solana, while the network’s tokenized equity market reportedly generated around $1.45 billion in July volume, representing approximately 82% of global tokenized-equity trading volume during the period.These developments depend heavily on deep stablecoin liquidity since tokenized securities, payment products and DeFi markets require efficient on-chain settlement.Also Read: Kamino Launches Solana USDC Vault: Here’s What Traders Should KnowStablecoin Market Could Expand FurtherThe wider opportunity remains significant. Morningstar estimates that the global stablecoin market could reach approximately $1.45 trillion by 2035, compared with roughly $300 billion currently.The growth is expected to come from crypto trading, cross-border remittances, business payments and emerging-market demand for dollar-denominated assets.If stablecoin adoption continues expanding, Solana’s existing $16.7 billion supply base and hundreds of billions of dollars in monthly transfer volume could position the network as one of the primary beneficiaries.For Solana, the stablecoin boom is therefore becoming more than a DeFi story. It is increasingly developing into an infrastructure thesis built around payments, settlement and tokenized finance.FAQs:1. How large is Solana’s stablecoin market in 2026?Solana’s stablecoin supply stands at approximately $16.7 billion as of August 2026. That represents more than 11x growth from roughly $1.5 billion three years earlier.2. Which stablecoin dominates the Solana network?USDC is the dominant stablecoin on Solana, accounting for approximately 75%-80% of total stablecoin supply. USDT, PYUSD and yield-bearing stablecoins make up much of the remainder.3. How much stablecoin volume does Solana process?According to Artemis data cited in the research, Solana processed more than $500 billion in stablecoin transfers during July 2026. February volume had reached approximately $650 billion.4. Why is Solana attracting stablecoin activity?Solana offers fast settlement and relatively low transaction costs, making it suitable for payments, DeFi and tokenized assets. Its growing stablecoin liquidity also makes the network increasingly attractive for institutional applications.5. How large could the global stablecoin market become?Morningstar estimates the global stablecoin market could reach approximately $1.45 trillion by 2035, compared with around $300 billion currently. Payments, remittances and business transactions could drive growth.

Infrastructure Businesses: Building For Decades - Infrastructure businesses are positioned for long-term growth because roads, energy networks, data centres, transportation systems and digital connectivity require continuous investment. Their growth is often supported by government spending, urbanisation and rising commercial demand. While these businesses may require significant capital upfront, their essential nature can create predictable revenue opportunities and long-term contracts that provide stability through changing economic cycles.Healthcare Businesses: Serving Essential Needs - Healthcare businesses benefit from demand that remains relatively consistent regardless of broader economic conditions. Hospitals, diagnostics companies, pharmaceutical firms, medical technology providers and specialised healthcare platforms address essential needs. Ageing populations, increasing health awareness and expanding healthcare access can support sustained growth. Businesses that combine quality services with technology and affordability can build strong customer trust and remain relevant for decades.Technology Businesses: Scaling Through Innovation - Technology businesses can achieve long-term growth when they solve persistent problems instead of chasing temporary trends. Software platforms, cybersecurity companies, cloud services and enterprise technology providers can benefit from recurring demand as businesses digitise operations. Strong technology companies continuously improve their products, expand into new markets and develop recurring revenue streams. This creates opportunities for scalable growth without depending entirely on short-term consumer excitement.Financial Services: Building Customer Trust - Financial services businesses can create lasting value by addressing everyday needs such as payments, banking, insurance, lending, investments and wealth management. Customer trust becomes a significant competitive advantage because financial relationships often continue for years. Companies that combine technology, convenience, security and responsible financial products can build strong customer retention. Growing incomes and increasing financial participation can further expand their long-term opportunities.Consumer Businesses: Creating Everyday Demand - Consumer businesses can achieve sustainable growth when they sell products customers repeatedly need or genuinely value. Food, personal care, household products and other everyday categories benefit from recurring purchases and large addressable markets. Strong brands can strengthen customer loyalty while distribution expansion creates additional opportunities. Companies focused on product quality, affordability and changing consumer preferences are better positioned for long-term relevance.Renewable Energy: Preparing For The Future - Renewable energy businesses are targeting a structural shift in how electricity is produced and consumed. Solar, wind, battery storage and related technologies could benefit from growing electricity demand, energy security concerns and global efforts to reduce emissions. These businesses require substantial investment, but long project lifecycles and expanding clean-energy infrastructure can create durable opportunities. Innovation and falling technology costs could further support growth.Education Businesses: Investing In Human Capital - Education businesses address a long-term need: helping people acquire knowledge and skills throughout their lives. Universities, vocational platforms, professional training companies and online learning services can benefit from changing employment requirements and demand for continuous upskilling. Businesses offering practical, affordable and recognised learning can build lasting customer relationships. Their opportunities may expand further as artificial intelligence reshapes workplace skills.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Tata Group’s stocks faced selling pressure in India on Wednesday after N Chandrasekaran resigned as chairman of Tata Sons. The decision came on August 12, ahead of the August 18 AGM. Chandrasekaran is said to continue his responsibilities until February 2027. Investors reacted by selling major Tata shares as uncertainty in leadership raised questions about the group's future strategy.TCS led the decline, falling 4.55% to Rs 2,336.90 on the NSE around 11:05 a.m. Tata Consumer Products dropped 1.6%, while Titan Company slipped 1.3% during the session. Tata Steel and Indian Hotels also declined, while Tata Technologies and Tata Investment Corporation fell up to 1%.The market reaction followed Chandrasekaran's decision not to seek another term as the chairman. Tata Sons previously faced uncertainty over his reappointment before the August 18 shareholder meeting.Reports also linked the situation to differences involving Tata Trusts Chairman Noel Tata. Tata Trusts holds about 66% of Tata Sons, giving the group significant influence over major leadership decisions.Chandrasekaran joined Tata Group in 1987 and became the chief executive of TCS in 2009. He took charge of Tata Sons in 2017 and later guided major expansion across several businesses.The leadership change occurs at a time when Tata Group is pursuing massive investments in technology, semiconductors, aviation, electric vehicles and digital businesses. Investors therefore seek clarity on succession and capital allocation.A senior official close to Shapoorji Pallonji Group urged stakeholders to protect the institution's long-term interests. “Personal or historical differences should not be allowed to overshadow what is in the long-term interest of Tata Sons.”Broader market weakness added pressure, with higher crude prices hurting sentiment. Around 11:15 a.m., both Sensex and Nifty fell by 0.69%.The immediate stock decline reflects governance uncertainty rather than a sudden deterioration in operating performance. Market attention now shifts toward the succession process and the August 18 AGM.Also Read: TCS Flags Employee Data Exposure, Customer Data SafeJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

IntroductionThe FPV drone industry has developed quickly and pilots have more options than ever before. There are a variety of different types of drones, each with its own specific purpose, from compact indoor drones to high-performance freestyle and cinematic platforms. This may be a good thing for consumers, but it can also make it more difficult for consumers to purchase. A high-performance racing drone might not be the ideal choice for videography, and an easy-to-flown drone might not be capable of the latest in flight-control technology.The first step to picking the right FPV drone is to determine where and how you will be using it. When buying a plane, it is important to take into account not just specifications or price but also the flight style, skill level, upgrade potential and long-term value. Whether you are just getting started on the windsurfing journey or an experienced sailor, having a well matched drone is beneficial to your flying and will save you money and time. Droneer Shop supplies everything you need from new FPV pilots to veteran ones in terms of FPV drones, FPV drone kits, replacement parts, and accessories. The purpose of this guide is to break down the important considerations to make and ensure you select equipment that will help you achieve your goals now and for future skill development.Understand Your Flying Purpose Before Choosing a DroneFirst of all, your primary purpose of flying the drone should determine the type of FPV drone you get. A few pilots may be interested in competitive racing, which requires speed and being light and responsive. Others like freestyle flying, which emphasizes on flying tricks, creative flying and precise control. Cinematic FPV drones are preferred by content creators as they generate smooth and controlled footage, perfect for travel videos, real estate, and commercial shoots.The place you're flying in is also crucial. Small drones with ducted propellers work best in an indoors setting or in confined areas, while larger 5-inch drones work best in open fields with ample room to maneuver. For long-range enthusiasts, there is a need for bigger platforms with more powerful batteries and efficient propulsion systems for longer flights.When choosing a drone, it is important to think about how you will use it, or else you may end up disappointed with it. A racing drone might be too much for a new pilot and a cinematic drone might lack the responsiveness expected from a freestyle pilot. Knowing what you want to fly will help you to narrow your choices and to spend your money on equipment that performs the job you need done and not on capabilities that you may or may not use.Select an FPV Drone Kit That Matches Your Experience LevelA large part of figuring out what type of FPV setup is optimal for you is learning more about it through experience. A full FPV drone kit may be a better option for beginners as they do not have to select each part of the drone themselves and ensure they are compatible with one another. These kits usually come with a set of radio transmitter, batteries and their chargers, and FPV goggles or display equipment, which minimizes compatibility hassles during setup.A package that is ready to fly also lets new pilots use more time to practice without having to spend time fixing technical issues. There are a lot of entry level kits that come with the flight controller already preprogrammed and the radio already prebound, so the learning curve isn't too steep. Self-leveling flight modes and reliable failsafe settings are also features that can help instill confidence during the initial learning of basic flight control.More advanced pilots typically like more flexibility. They would rather buy parts rather than ready-to-fly kits that are finished, and then add additional parts to their kits to make them look the way they want. More common upgrades are higher power brushless motors, sturdier carbon fiber frames, better antennas, better performing electronic speed controllers, and larger capacity LiPo batteries. The changes can be made to make the plane faster, stronger, more efficient, or to give it better flight qualities, depending upon the pilot's goals.Droneer Shop provides options for both new FPV users and seasoned professionals, ensuring that users can select the right gear to suit their proficiency level and also have options for future enhancements. It is important that you know what kit to choose from the start as this will make for a more seamless learning experience and give you a better starting point as you begin to learn about FPV technology.Evaluate Flight Performance and the Video Transmission SystemFlight performance is not just reliant on motor power. The type of frame, the type of propellers, the battery voltage, flight controller tuning and the type of the video transmission system all affect the behavior of a drone in the air. Knowing these components enables buyers to make informed comparisons about performance in real-world situations, not just on the marketing claims.One of the most obvious differences between FPV drones is their frame size. These compact three-inch drones are light and agile, suitable for smaller flying environments. The five inch drones are the ones that are most popular since they are fast, stable, and durable. 7-inch models are typically chosen for extended journeys and those looking for more distance might opt for the larger size.Another important item which directly influences the flight experience is the video transmission system. The idea of FPV viewing system is significantly different from the obsolete concept of FPV viewing system; rather than relying on the camera to display the footage, modern FPV system is a system of video transmission from the camera to a receiver or a compatible FPV system of goggles. The most popular alternatives are analog and digital systems.Pilots, particularly in competitive racing, still prefer analog systems as they offer the lowest latency associated with their operation, enabling the pilot to respond swiftly in high-speed flight. Digital systems, however, offer much sharper pictures, more detail and greater overall picture quality, and are the preferred choice for freestyle pilots and aerial film makers who demand clarity.The other crucial element is the FPV video transmitter (VTX), which transmits the real-time video feed from the drone. Safety is ensured by selecting an adequate VTX in terms of power output and the correct antenna configuration for the type of flight. These components combine to provide a more stable and fun FPV experience, and minimize signal loss during challenging flights.Compare Camera Quality, Battery Performance, and Drone DurabilityA good FPV drone will offer a sweet spot of reliability, flight time, and durability. These three things have a stronger influence on their overall ownership experience, but speed is exciting. When ordering parts, it is wise to select pieces that are suitable to the flying style to help keep the maintenance expenses low and to guarantee the drone works properly in various environments.The onboard FPV camera feeds the live video stream of the drone, which is then transmitted via the video transmission system. With a camera that offers excellent image clarity, colour and low light capabilities, pilots can make more confident decisions on distance when flying through obstacles or when producing cinematographic footage. Some pilots have a preference for digital FPV systems, as they offer a more detailed live feed and offer higher image quality. Analog systems could continue to be used by racing pilots because they have a lower latency period and can be helpful during high-speed flights where quick reactions are important.Another key element to consider is battery performance. FPV drones are almost always powered by LiPo batteries because they provide the power that is necessary for fast acceleration, and fast response time in handling. The duration of flight will depend on the size, flying style, flight time of the drone's battery and weather conditions. There is usually a greater amount of power required for freestyle flying and racing than for smooth cinematic flights, so it's a good idea to have a couple extra batteries on hand for longer flights.Lastly, the durability also should not be ignored, particularly for beginners. FPV flying is an educational process, which often means crashes, a good carbon fiber frame and well-made electronics are all nice to have. An arm, motor and propeller that can be replaced is less expensive and easier to repair than a major replacement after minor impact damage. Droneer Shop provides replacement parts and accessories to ensure that pilots can maintain their equipment in top condition and prolong the life of their asset.Fly Responsibly with Proper Safety Practices and Regular MaintenanceIt is just as crucial to establish safe flying habits as it is to select the appropriate equipment. Even the most advanced FPV drone can be best perfected run when it is checked before every flight and when it is operated under proper environmental conditions. Many problems can be avoided during pre-flight and problems with equipment can be avoided by doing a quick pre-flight check.Prior to departure pilots should ensure that the propellers have been securely fitted, the battery is fully connected, the FPV video transmitter antenna is correctly fitted and that the radio link is working. If you fly without these components you can lose the signal, or have signal that is less stable. The weather should also be taken into account. Poor weather conditions such as high winds, rain, and low visibility can be challenging to fly in, especially for novice pilots.Knowing local drone laws is also a crucial aspect of responsible drone FPV flying. There are several countries with regulations on maximum altitude, airspace restrictions, airport safety zones, and drone registration. Obedience to these rules ensures the safety of the pilot and others, and will help preserve the good name of the FPV community.To make drones operate at their best, they need regular maintenance. Small problems after a flight such as a damaged frame, a motor problem, a broken propeller or a failing battery should be avoided by cleaning up before and after each flight, changing propellers as they wear out, checking the motor, and evaluating the health of the battery. In the long run, pilots who develop these habits will experience greater reliability and will incur less maintenance costs.Buy from a Trusted Drone Retailer for Long-Term ValueThe location where you buy your FPV drone is nearly as crucial as the drone itself. A reputable retailer can provide authentic parts, service, and replacement components which could be required as your expertise grows. The quality of the components or compatibility problems can occasionally arise, and the assistance provided by the seller may be restricted.Specialized retailers are technically savvy and know the difference between the different FPV systems and can assist customers to pick products that fit their objectives. If you want to build a drone for beginners, or freestyle, or racing, or parts, there's no need for guesswork with expert guidance. Compatible batteries, FPV video transmitters, antennas, chargers, and parts are also available at reliable retailers, allowing for convenient maintenance in the future.From FPV drones and accessories to replacement parts, Droneer Shop equips pilots with a range of carefully chosen products tailored to various skill levels. Availability of knowledgeable support and authentic products offers more confidence over the ownership journey. Rather than a hassle of compatibility issues, pilots can hone their abilities and have more successful flights.ConclusionComparing prices and technical specs isn't enough to pick the right FPV drone. The better your overall flying experience, the more you understand about your flying goals, the more knowledge you have about the equipment, the more you know about the flight performance, and the more you know about the appropriate video transmission system, the better. Considerations of battery quality, durability, maintenance and safety also help to ensure that your investment lasts and you continue to enjoy the hobby.Droneer Shop provides a convenient service for both new and old users to buy high-quality FPV drones, FPV full drone kits, replacement parts, and professional accessories. With some investment in good gear and understanding of the basics of FPV technology, you can create something that will continue to work as you become more proficient. By making an informed purchase today, they'll find that they have a better, more reliable, and more satisfying FPV flying experience for years to come.

Ethereum (ETH) could stage a substantial recovery before the end of 2026 if falling exchange reserves, expanding staking and institutional adoption translate into tighter liquid supply. Google Gemini projects a bullish year-end range of $4,000-$6,000, compared with a baseline price around $1,876.Reaching the lower end of that forecast would require ETH to gain approximately 113%, while $6,000 would represent an increase of about 220%. However, Gemini also outlines a bearish scenario in which ETH could revisit $1,100-$1,500.Gemini Sees an Ethereum Supply ShockSupply dynamics form a central part of Gemini's bullish thesis. Ethereum exchange reserves are around record lows, meaning fewer coins are immediately available for trading.At the same time, staking continues to remove base ETH from liquid circulation. Corporate treasuries and institutional investors increasingly have the option to stake their holdings, turning ETH from a purely appreciating asset into one capable of generating staking rewards.Gemini expects declining exchange balances combined with increased staking to potentially create a supply shock if demand accelerates.Institutional adoption represents another catalyst. Continued growth in spot and yield-bearing Ethereum products could introduce additional demand, while expansion in stablecoins and real-world asset tokenization could strengthen Ethereum's role as financial infrastructure.ETH Must First Reclaim $2,000Despite the long-term bullish forecasts, Ethereum’s present technical setup remains considerably weaker.ETH trades at $1,885.91 with an increase of 0.72% in the last 24 hours. ETH decline started from roughly $4,850 back in August 2025 to the current level, representing around a 61% drawdown.The pressure picked up in early 2026. ETH drifted down around $1,880 in February, then managed to climb back near $2,400 by May. After that, there was another leg lower, pushing the token toward the June trough around $1,530.Recent price action has been improving as the token formed higher lows in July and continued in August.On the downside, near-term support shows up around $1,850, followed by $1,600, and a deeper support at $1,530, the June low. On the upside, resistance seems to cluster near $1,930, then the more important $1,930 level, followed by the psychologically important $2,000 mark. The Relative Strength Index (RSI) is at 51.71, indicating largely neutral momentum rather than a confirmed bullish trend.Also Read: Ethereum Whale Adds 121,000 ETH as BitMine Expands its HoldingsEthereum’s 2026 outlook matters as its price increasingly depends on more than speculation. Exchange supply is falling, staking participation going is up, and institutional adoption could tighten liquidity. However, ETH still has to reclaim a few key technical levels for that optimistic $4,000-$6,000 outlook to become reality.Why this Matters?What Could Send ETH Toward $4,000-$6,000?Gemini's bullish scenario depends on several catalysts occurring together. Successful Ethereum network upgrades, stronger institutional flows, increasing staking participation and continued real-world asset and stablecoin adoption could strengthen demand.A shift toward easier global monetary policy could provide another boost by increasing liquidity available for risk assets. Gemini also expects a bullish environment to potentially drive a recovery in the ETH/BTC ratio.The downside scenario remains significant. Persistent macroeconomic pressure, developers migrating toward competing Layer-1 networks and Layer-2 activity reducing Ethereum mainnet fee capture could limit ETH's recovery.Under that bearish scenario, Gemini sees $1,100-$1,500 as a potential retest zone. For now, $2,000 represents the first major test. A sustained move above that level would provide stronger evidence that Ethereum's improving supply dynamics are beginning to translate into price momentum.FAQs:1. What is Google Gemini's Ethereum price prediction for 2026?Google Gemini projects a bullish year-end range of $4,000-$6,000 for Ethereum. From around $1,876, reaching those targets would require gains of approximately 113% to 220%.2. Could Ethereum reach $6,000 in 2026?Gemini sees $6,000 as possible under a bullish scenario involving stronger institutional demand, increased staking and successful network upgrades. Improving macroeconomic liquidity could provide additional support.3. What is the bearish Ethereum price prediction for 2026?Under a bearish scenario, Gemini sees ETH potentially falling toward $1,100-$1,500. Persistent macro pressure, Layer-1 competition and weaker mainnet fee capture could contribute to this downside.4. Why could Ethereum staking support ETH prices?Staking removes ETH from immediately tradable base supply and provides holders with staking rewards. Combined with declining exchange reserves, higher staking participation could tighten liquid supply if demand increases.5. What are the important Ethereum price levels to watch?Immediate support sits near $1,850, followed by $1,600 and $1,530. On the upside, ETH faces resistance around $1,930, with $2,000 representing the key psychological level for a stronger recovery.

Selling a software business is not like selling a manufacturer or a services firm. Recurring revenue, net retention, and margin change how buyers model value, and which advisor is equipped to run the process. A generalist bank can move a deal, but it will not always know how a strategic acquirer reads your churn cohorts or why your ARR mix matters more than a single revenue number.This guide ranks five M&A advisory firms that genuinely serve technology and software companies, for founders weighing a sell-side process. It leads with a boutique that concentrates on exactly that work.Key TakeawaysL40 Partners is the top pick for founder-led technology and software companies, with 180+ transactions closed across Europe and North America and a sector-focused, cross-border process. Recent deals include KrakenD, FirstPromoter, and Big Red Cloud. The four firms that follow are strong technology advisors for different situations, summarized in the comparison table below.How We EvaluatedWe scored each firm against five weighted criteria. The weights reflect what moves outcomes for a software founder running a sale, rather than brand size alone. Inputs came from firm websites, PitchBook and Crunchbase deal records, and public transaction announcements.Sector focus and technology expertise (30%): depth in software and SaaS specifically, not technology as a side category.Deal track record (25%): history of closed sell-side and advisory transactions in the software space.Cross-border capability (20%): ability to reach international strategic and financial buyers, not only domestic ones.Process and valuation rigor (15%): discipline in positioning, buyer outreach, and defending value through diligence.Cultural fit for founder-led companies (10%): willingness to work closely with founders rather than treat them as one file among many. Weights sum to 100%.Comparison at a glance1. L40 PartnersL40 Partners is a boutique M&A advisory firm built around technology and software companies, with a focus on sell-side advisory for founders in the lower middle market and mid-market. Rather than covering every sector, the firm concentrates on software and SaaS businesses, where recurring-revenue mechanics and product positioning drive the valuation conversation. That focus is the point: a founder gets an advisor whose default frame of reference is software economics.The firm is led by CEO and Partner Juan Ignacio García Braschi, who brings more than 20 years of experience and previously co-founded and served as CFO of Cabify, helping scale it from roughly $1M to around $800M in revenue. That operator background shapes how L40 runs a process. The firm has closed 180+ transactions across Europe and North America in SaaS, marketplaces, and adjacent software, with recent deals including KrakenD, FirstPromoter, and Big Red Cloud, and it publishes its own SaaS valuation and M&A data drawn from that deal history. Its cross-border reach matters when the most motivated buyer for a software company sits in a different market than the seller.Focus: Sell-side M&A advisory for technology and software/SaaS companies in the lower middle market and mid-market.Best for: Founder-led software businesses that want a sector-focused advisor and access to cross-border buyers.Notable: 180+ transactions closed across Europe and North America; recent deals include KrakenD, FirstPromoter, and Big Red Cloud; led by CEO and Partner Juan Ignacio García Braschi, former Cabify co-founder and CFO.2. Software Equity GroupSoftware Equity Group is a sell-side advisory firm that works almost entirely with software and SaaS companies. Its narrow focus means the team spends its time on the metrics that software buyers care about, and it publishes research on SaaS M&A trends that founders often use as a reference point before going to market.Focus: Sell-side M&A advisory dedicated to software and SaaS companies.Best for: Founders who want an advisor working exclusively inside the software category.Notable: Known for regularly published SaaS and software M&A market research.3. Union Square AdvisorsUnion Square Advisors is a technology-focused investment bank that advises on M&A and capital-raising across software and other technology sectors. The firm tends to work with growth-stage and established technology companies and maintains relationships with both strategic and financial buyers.Focus: Technology-sector M&A and strategic advisory across software and adjacent categories.Best for: Established technology companies that want a specialist bank with strong buyer relationships.Notable: Independent advisory model concentrated on the technology sector.4. GP BullhoundGP Bullhound is a technology-focused advisory and investment firm with a strong international presence. It advises technology companies on M&A and financing, and its cross-border reach makes it a common choice for founders who expect interest from buyers in multiple regions.Focus: Technology M&A and growth advisory with an international footprint.Best for: Technology companies expecting cross-border buyer interest.Notable: Recognized for its coverage of European and global technology markets.5. Drake Star PartnersDrake Star Partners is a global advisory firm in the technology and digital-media sector that handles M&A and private capital transactions. It works across a broad set of technology subsectors and operates from multiple offices, giving founders access to buyers beyond a single market.Focus: M&A and capital advisory across technology and digital media.Best for: Technology and digital-media companies wanting broad subsector coverage.Notable: Global office network spanning several technology hubs.FAQsWhen should a founder hire an M&A advisor?Most founders bring in an advisor before they start talking to buyers, not after. Engaging early gives the advisor time to prepare positioning, clean up the numbers a buyer will scrutinize, and build a wider list of qualified buyers, which usually produces a more competitive process than reacting to a single inbound offer.What is the difference between sell-side and buy-side advisory?Sell-side advisory means the firm represents the company being sold and works to maximize the outcome for that seller. Buy-side advisory means the firm represents an acquirer looking for and evaluating targets. A founder selling a company wants a sell-side advisor whose incentives are aligned with the seller.How are M&A advisors typically paid?Most sell-side engagements combine a retainer with a success fee that is paid on close and calculated as a percentage of deal value. Structures vary by deal size and firm, so founders should confirm the fee arrangement, any minimums, and what happens if the process does not close before signing an engagement.

Ahead of Independence Day, PayU advances digital inclusion by enabling more people to make online payments independently.New checkout includes features like screen-reader optimisation, adaptive user profiles, visual inclusivity modes, and text resizingPayU merchants can offer Accessible Checkout without changing existing integrations, seamlessly expanding their ability to serve every customer, regardless of their abilityGurugram, 12 August 2026: PayU, India's leading diversified fintech platform, today announced the launch of Accessible Payments Checkout, India's first RBI-compliant payment checkout designed for people who are blind or visually impaired. The launch marks a significant step towards making digital payments more accessible and inclusive. As the country celebrates Independence Day, the launch reinforces the importance of ensuring that everyone can participate in the digital economy with greater independence.With this launch, PayU becomes the first payment gateway in India to comply with the Reserve Bank of India's October 2024 accessibility mandate (BIS IS 17802). The enhanced checkout introduces a range of features designed to improve discoverability, navigation, and interaction for users with visual and cognitive accessibility needs, making the online payment journey more seamless and intuitive.The solution reflects PayU's continued commitment to building inclusive financial technology and enabling every user to access digital payments with confidence and ease.The new PayU Accessibility Checkout includes four key features:Full-Screen-Reader Optimisation: PayU’s Accessibility Checkout is engineered to work seamlessly with screen readers, ensuring easy navigation of the entire payment journey for the visually impaired and blind without any sighted assistance. From choosing the payment method like Net banking, UPI, QR, NEFT, etc. to payment amount confirmation and transaction completion, every element on the checkout page is clearly and transparently announced via voice commands to the user, ensuring they know where exactly they are in their payment journey.  Adaptive User Profiles: This feature allows users to customize their checkout environments – adjusting cursor size, button dimensions, and navigation aids to fit their requirements. Their preferences can be saved, switched between or reset at any point. The checkout adapts as the user wants, delivering complete control in the hands of the user.Visual Inclusivity Modes: To aid users with conditions such as low vision, colour blindness, or light sensitivity, a wide variety of visual modes are offered by PayU’s Accessibility Checkout. From high contrast to greyscale mode to colour inversion to saturation adjustment options, the checkout offers support to the visually impaired users who rely on colour and contrast adaptations to use digital platforms.Text Resizing: The Accessibility Checkout supports text scaling of up to 200% of the standard size, without overlapping or hiding any content. This feature ensures all elements on the checkout is transparently seen and read by the users with visual impairments. "True financial inclusion is only possible when every individual can access and use digital payments independently. At PayU, accessibility is not an afterthought - it's a core design principle. With the launch of our Accessibility Checkout, we're helping merchants deliver payment experiences that are inclusive by design while enabling millions of users with diverse accessibility needs to participate more confidently in India's digital economy. This is an important step towards supporting the RBI's accessibility vision and building digital infrastructure that works for everyone," said Manas Mishra, Chief Product Officer, PayU and Wibmo.Prashant Ranjan Verma, General Secretary, National Association for the Blind, Delhi, said, “I appreciate PayU's efforts to make digital payments more accessible for everyone, including people who are blind or have low vision. I was able to complete a UPI payment independently using PayU's accessibility-first checkout with VoiceOver. I hope PayU continues to strengthen accessibility so that more people with visual impairments can transact confidently and independently."PayU’s Accessibility Checkout does not require merchants to change their existing integrations. Accessibility is embedded as a design feature allowing merchants using PayU to automatically offer a compliant and accessibility-first payments checkout experience to their customers with disabilities.About the RBI Mandate:The Reserve Bank of India's October 2024 circular mandates digital payment providers to ensure their digital products and services, including websites, mobile applications and software, comply with the Bureau of Indian Standards, BIS IS 17802, accessibility standards for persons with disabilities.

iPhone 18 Pro: Apple is expected to introduce the iPhone 18 Pro with a faster chip, camera upgrades, improved display, and refined design.iPhone 18 Pro Max: The flagship iPhone 18 Pro Max could bring a larger display, enhanced cameras, stronger battery performance, and advanced processing capabilities.iPhone Ultra: Apple may unveil its first foldable iPhone, reportedly featuring a large internal display, premium design, and high-end specifications.Apple Watch Series 12: The next Apple Watch could receive performance improvements, health-focused features, design refinements, and a new generation of connectivity options.Apple Watch Ultra 4: Apple may refresh its rugged smartwatch with improved performance, longer battery life, enhanced durability, and updated health-tracking capabilities.Apple TV 4K: A refreshed Apple TV 4K is reportedly under consideration, potentially bringing faster processing, improved connectivity, and better smart-home integration.HomePod mini: Apple could update the HomePod mini with improved audio performance, smarter Siri capabilities, and deeper integration with its expanding home ecosystem.Smart Home Hub: Apple may introduce a dedicated smart-home hub designed to connect devices, control household accessories, and provide easier access to Siri-powered features.Read More StoriesJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

By Saravanan Balasundaram, Founder & CEO, Han Digital SolutionAs enterprises move from deploying AI to managing autonomous AI agents, a new engineering capability is beginning to take shape, and it could redefine what technology teams look like over the next few years.Not too long ago, the industry was focused on Prompt Engineers, professionals who helped users interact more effectively with AI models. More recently, the rise of Forward Deployed Engineers (FDEs) marked another important shift. Embedded within client organizations, these professionals build, customize, and deploy AI solutions, helping enterprises move AI from experimentation to real-world business applications.As AI continues to evolve, we are witnessing yet another defining shift. The next frontier is no longer about writing better prompts or deploying AI faster. It is about building AI systems that can operate independently, while interacting with models, evaluating outcomes, and deciding what to do next without waiting for human intervention, all while doing so reliably, responsibly, and at scale. The industry has begun to call this Loop Engineering.The term is new, but the problem behind it isn’t.Enterprises today have access to powerful AI models, and the challenge is no longer simply building AI capabilities; it is making them work effectively inside complex business environments. AI systems need to interact with enterprise workflows, collaborate with other AI agents, validate outcomes, recover from failures, and understand when human intervention is required.The next phase of enterprise AI will move beyond individual assistants that help employees summarise documents or generate code. We are moving towards a world where multiple AI agents will collaborate across software development, cybersecurity, finance and other core business operations.As enterprise AI moves from individual applications to interconnected systems of autonomous agents, the nature of software engineering work itself is changing. The focus is shifting from building AI capabilities in isolation to designing frameworks, workflows and guardrails that allow multiple AI systems to operate together reliably at scale. And the evolution of AI talent is also following this progression.Unlike earlier AI roles, Loop Engineering will not be defined by one specialized skill. It will require professionals who can combine AI engineering with systems thinking, workflow design, business context and governance.And if we look more closely, several shifts are accelerating this transition.With India’s Global Capability Centres (GCCs) becoming ownership centers for products, platforms and business-critical innovation, this shift is changing the talent equation too; thereby creating demand for engineers who can combine AI expertise with enterprise engineering capabilities across areas such as platform architecture, data engineering, automation, MLOps, and business workflows. The GCC workforce of the future will not just execute technology roadmaps created elsewhere; it will increasingly shape products, platforms and innovations that drive global businesses. This is reflected in hiring patterns, with nearly two-thirds of new GCC roles requiring GenAI, data engineering or intelligent automation capabilities.This demand is no longer confined to Global Capability Centres (GCCs). IT services firms of every size are redesigning their delivery models around agentic AI to stay ahead of evolving client expectations, while AI-native startups are building orchestration platforms, agent frameworks and tools that make Loop Engineering possible at scale. Across GCCs, IT services firms, platform companies, and AI startups, one talent need is becoming increasingly clear: engineers who can operate above the prompt layer by designing, orchestrating, and continuously optimizing intelligent AI systems.Loop Engineering capability itself is still nascent. In India, the currently countable pool of engineers who can design and operate these agentic loops is small. Still, with upskilling programs targeting this gap, that pool is expected to cross 10,000 professionals in 2-3years, as customers move from single-shot AI deployments to the next stage of always-on, agentic systems.At the same time, enterprises cannot build the next generation of AI systems by starting from scratch. Platforms such as SAP, Oracle, Microsoft, Pega, ServiceNow, and Guidewire continue to power critical business processes across industries. However, the challenge is that talent combining deep enterprise platform expertise with AI capabilities has not scaled at the same pace as adoption. Therefore, the next generation of technology professionals will need to bridge this gap, bringing AI into enterprise applications and creating intelligent workflows that deliver measurable outcomes.The growing complexity of enterprise AI is also accelerating the need for stronger governance, automation, security and responsible adoption. As organizations deploy AI systems across critical business functions, they will need professionals who can build the right controls around data, identity, compliance and decision-making. India’s evolving data protection landscape will further reinforce this need as enterprises focus on deploying AI systems that are not only efficient, but also trusted and accountable.Given that India’s technology services model is shifting from delivering just outcomes to delivering global value, the value of talent will increasingly lie in designing intelligent systems, solving complex business problems and creating measurable impact. This is precisely where the next generation of AI engineers, including Loop Engineers, will create value.Whether the industry eventually calls this capability Loop Engineering, AI Orchestration or something else is secondary. What matters is that enterprise AI is entering a new phase, and organizations that build adaptable talent ecosystems will be better positioned to lead it.The half-life of technology skills is shrinking faster than job titles can keep pace. A role that does not exist today can become mission-critical tomorrow. And while we know that India’s advantage will not come from chasing every new AI title after it emerges, but will come from building a workforce and delivery ecosystem capable of adapting before the next role even has a name.

Google’s Gemini app has crossed 1 billion monthly users, marking a major step in the AI chatbot race. Sundar Pichai announced the milestone on August 11, 2026, through X. Pichai called Gemini “our fastest growing product ever” while sharing the milestone on X. "1B+ people are now using @Geminiapp every month to spark new ideas and get things done," he wrote on X.“Kudos to @JoshWoodward & the entire Gemini team, and thank you to everyone who has been on this journey with us,” the CEO added.1B+ people are now using @Geminiapp every month to spark new ideas and get things done. It’s our fastest growing product ever, and our 14th to hit the 1B-user mark.Kudos to @JoshWoodward & the entire Gemini team, and thank you to everyone who has been on this journey with us -… pic.twitter.com/sSWrULX4Qn— Sundar Pichai (@sundarpichai) August 11, 2026   The achievement also makes Gemini the 14th Google product to cross 1 billion users. Gemini had 750 million monthly users in February before reaching 950 million in July. The company said Gemini reached the mark faster than any other product of theirs, adding Android access, Google services, image tools and special offers helped drive fast growth.Gemini has grown quickly through Android, Chrome, Workspace and other Google products. This gives the AI chatbot access to millions of existing users without requiring separate app searches. More than 100 million Gemini users also access the app through Apple devicesGoogle added that consumers used their voice rather than typing to access Gemini. Around 63% of users talk to Gemini through voice while using the app. The AI platform also creates more than 150 million images each day for different creative tasks.This milestone puts Gemini close to ChatGPT in the global AI race. ChatGPT also crossed 1 billion monthly users earlier this year, according to recent reports. The comparison needs care since both companies use different ways to measure users. Also Read: Google Warns of Hackers Targeting US Financial Firms with Fake CallsJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Key Takeaways :HDFC Bank, Kotak Mahindra Bank and SBI Life show how Agentic AI has moved from experiments into real BFSI workflows.Credit, underwriting, fraud investigation, claims and customer service offer some of the strongest opportunities for AI agents.RBI’s evolving framework places strong emphasis on human oversight, accountability, explainability, security and model risk controls.India’s banking, financial services and insurance sector has moved beyond basic chatbots and simple automation. Agentic AI now has a place in credit, underwriting, fraud checks, customer service, claims and internal operations. Unlike a conventional chatbot, an AI agent can understand a task, collect information, use digital tools, follow several steps and send complex cases to a human employee.The shift has strong business value. EY data show that 74% of Indian financial firms had started GenAI proof-of-concept projects, while 11% had already moved GenAI into production. Around 42% had also allocated budgets for GenAI. EY estimates that financial services could gain 34–38% productivity by 2030, while banking operations could see productivity gains of up to 46%.Banks Move From Chatbots to AI AgentsIndian banks now focus more on workflow automation than simple customer conversations. An AI agent can collect customer documents, read financial information, check internal rules, review credit data, prepare a recommendation and send an unusual case to a credit officer. Such a process can cut manual work while keeping a human employee in control of important decisions.HDFC Bank provides one of the clearest examples. Its April 2026 disclosure reported five AI-agent use cases in production and another 14 under development. The bank has built an internal AI platform with Agentic Studio and Agentic Mesh, along with enterprise search, document extraction, voice agents, model evaluation and governance tools. HDFC Bank also reported 97% digital adoption for payments and service transactions and 92% digital adoption for acquisition journeys. This digital base gives the bank more scope to use AI inside complex processes.Kotak Mahindra Bank has taken a more focused route. The bank has built around 20–25 standalone AI agents for areas such as credit-bureau analysis, document intelligence, OCR, financial-statement analysis and employee support. One agent can review a credit-bureau report of about 20 pages and create a useful summary for a credit analyst. Kotak keeps human employees in the decision loop, which suits the high-risk nature of financial services.Credit and Lending Get a Major AI OpportunityCredit underwriting stands among the most valuable areas for Agentic AI. A credit agent can collect documents, examine bank statements, check bureau information, compare details with lending rules and prepare an initial credit view. It can also spot missing information and send unusual cases to a human officer.This model can help banks reduce the time needed for loan assessment. It can also help lenders study customers with limited formal credit records. RBI Governor Sanjay Malhotra recently said AI could help lenders use information such as cash flows, GST filings and utility-payment records. Such data could expand access to formal credit for customers who do not fit traditional credit models.Also Read - Generative AI and Regulatory Compliance in the BFSI SectorInsurance Finds Strong Use CasesInsurance offers another major opportunity for Agentic AI. Underwriting and claims contain large amounts of documents, rules and risk information. An AI agent can read medical reports, extract important facts, check policy rules, identify missing details and prepare an underwriting recommendation.SBI Life has adopted Datamatics’ TruAI Underwriting, an Agentic AI solution for risk assessment. The system can study medical histories, laboratory reports and several risk indicators. The use case shows how Indian insurers have started to take AI into core business decisions rather than limiting it to customer support.ICICI Lombard also has a broad AI strategy across underwriting, claims and customer service. Its multilingual Voice AI platform has handled more than one million customer conversations. Axis Max Life has explored Agentic AI for underwriting, servicing and IT operations. EY estimates that insurance customer service could gain around 48% efficiency from AI.Fraud and Compliance Gain a New ToolFraud detection and anti-money-laundering work can also benefit from AI agents. A traditional system may flag a suspicious transaction, while an agent can take the next steps. It can collect customer history, review related transactions, compare several alerts, gather evidence and prepare a case for an investigator.An India-focused research project called CASE tested an AI agent with Google Pay India data and reported a 21% increase in scam-enforcement volume. The result shows the wider value of agentic systems: an agent can help gather information and support investigation rather than simply label a transaction as risky.RBI Sets Clear LimitsThe rapid rise of Agentic AI also creates new risks. RBI’s FREE-AI framework, released in August 2025, sets seven principles and 26 recommendations across infrastructure, policy, capacity, governance, protection and assurance. The framework stresses fairness, accountability, explainability, safety and human control.RBI’s June 2026 draft Model Risk Management guidance adds stronger requirements for AI models. Banks need clear records that support traceability, reproducibility and auditability. The guidance also highlights cyber risks, prompt injection, unauthorized access, external interfaces and unusual system use. Customer-facing AI should identify itself as AI, explain its limits and provide access to human assistance.Agentic AI can change how India’s BFSI sector handles credit, fraud, underwriting, claims and customer service. It can reduce manual effort, speed up decisions and widen financial access. Its impact could extend beyond cost savings, with AI helping banks and insurers serve rural customers, MSMEs and people with limited credit histories.Why this MattersAlso Read - Best Battery Sector Stocks in India for 2026 Investment GuideThe Next Phase of Indian BFSIIndia’s BFSI sector now stands at an important point. GenAI has moved into real business use, while specialised AI agents have started to handle parts of credit, underwriting, claims, fraud and service workflows. Yet fully autonomous financial decisions remain uncommon.The strongest model for India looks more like bounded autonomy than complete independence. AI agents can handle routine work, analyse large amounts of information and prepare decisions, while human employees retain control over high-risk outcomes.The biggest opportunity may come from rural customers, farmers, MSMEs and people with thin credit histories. SBI Chairman C.S. Setty recently highlighted AI’s potential for farm credit, alternative data, satellite information and rural financial access. RBI has also compared AI’s potential impact on lending with UPI’s impact on payments.India’s next BFSI AI phase will therefore focus less on impressive chatbots and more on AI agents that can complete real financial tasks. Banks and insurers that combine trusted data, strong digital infrastructure, secure system access and clear human oversight could gain the largest advantage from this shift.FAQs :1. What is Agentic AI in BFSI?Agentic AI refers to AI systems that can understand tasks, access relevant information, use digital tools and complete several steps with limited human intervention.2. How are Indian banks using Agentic AI?Banks use AI agents for credit analysis, document review, customer service, fraud investigation, employee assistance and other operational workflows.3. Which Indian banks have adopted Agentic AI?HDFC Bank and Kotak Mahindra Bank have publicly disclosed multiple AI-agent use cases across banking operations.4. How is Agentic AI changing insurance?Insurers can use AI agents for underwriting, claims, document analysis, customer service and risk assessment. SBI Life has already adopted an Agentic AI underwriting solution.5. What are the main risks of Agentic AI in BFSI?Key risks include inaccurate decisions, cybersecurity threats, data misuse, model risk, prompt injection and weak accountability, which makes human oversight essential.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Stefano Rosa has built his career around one question: how can emerging technology solve problems that existing systems were never designed to handle? His path has taken him from a small town in Italy to studying artificial intelligence and robotics in the UK, biomedical engineering at Imperial College London, machine learning and computational biology research, and eventually entrepreneurship.That combination of technical depth and firsthand startup experience now informs his work as co-founder of Choose Serene, where he is developing AI-powered automation for some of healthcare’s most persistent administrative challenges. Rather than focusing on AI as a conversational tool, Rosa is betting on a new generation of intelligent agents capable of working across fragmented healthcare systems and completing complex workflows autonomously.In this interview with Analytics Insight, Rosa discusses the evolution of his thinking from research to entrepreneurship, the lessons he learned while building and scaling companies, why sales matters as much as product, and how AI agents could fundamentally change the way healthcare operates.What inspired you to move from Italy to the UK and pursue AI and robotics? I like to remember that what really kick-started everything was reading Ray Kurzweil's How to Create a Mind. The book came out in 2012, but I picked it up in 2017. It planted this idea in my head that intelligence itself could be engineered, and that we were already on that path.And people at DeepMind were already showing the first signs of this idea. There was DQN learning to play Atari games straight from raw pixels, and then, right around when I read the book, AlphaGo beat Go, a game everyone thought was decades away from falling to a machine.So I started looking for where I could actually study it properly. Back then, the UK stood out; it had a handful of universities that offered AI as its own undergraduate degree, which was genuinely rare at the time. That was enough to make me pack up and move.How would you describe your journey from machine learning research to entrepreneurship in one sentence? Research is about invention, finding the gaps in what we understand; entrepreneurship is about innovation, finding the gaps between people and the solutions they needYou have worked across AI, neuroscience, biology, and biomedical engineering. How have these interdisciplinary experiences shaped the way you approach complex problems?The experiences have taught me how to solve problems where the answer isn’t obvious, and the data is never perfect.That’s been very useful as a founder. In healthcare, real-world workflows are messy. There are edge cases, broken processes, missing information, and systems that don’t always work as intended. I’ve learned not to design for the ideal case, but for what actually happens in practice.At Serene, that means we spend a lot of time understanding where things can fail and building around those realities from the start. My background has made me comfortable moving between technical details and the bigger problem we’re trying to solve, and making decisions even when we don’t have perfect information.What was the most valuable lesson you learned while working as a Data Scientist at dunnhumby? The most valuable lesson was learning to explain any idea in three sentences or lessYou built Wiredhub to over 600k in revenue with a team of eight. What were the key factors behind that growth? I’d say the biggest factors were perseverance, having a strong team, and being very focused on sales.We also had a product that solved a real problem. We listened closely to customers, kept improving it, and made sure the product got better over time rather than standing still.Customer loyalty was also a major driver of growth. Many customers stayed with us and kept buying, giving us a strong base to build on.And honestly, we were just very persistent. With a team of eight, everyone had to contribute, move fast, and keep pushing even when things were difficult.What does “building” mean to you personally? I love taking an idea in my head and turning it into something people can actually use, see, or experience. Especially with technology, there’s something exciting about creating a tool or product that works well, looks good, and makes someone say, “wow.”Building also means caring about the craft. Learning the tools, practicing for years, and paying attention to small details that most people may never notice but that make the final result feel right.Your journey includes both business growth and the challenge of not finding product-market fit. How did those contrasting experiences influence your mindset as a founder? Pre-PMF, you're in discovery mode. The goal is to generate noise. You do things even the hard way specifically because each one generates data you can use to triangulate toward what actually works. You need to generate noise to find patterns and figure out which direction to actually go.Growth is the opposite mode entirely. Once you have that signal, the job shifts to systems — thinking in terms of variables, processes, and feedback loops you can actually tune. It becomes about relentless optimization instead of relentless experimentation.What is one mistake that has made you a better entrepreneur? I used to underweight sales, assuming a great product would just sell itself. But that is more the exception than the norm. Getting that wrong taught me that sales and product are equally important and go hand in hand. Product is about making the “impossible” possible, and sales is about informing what 'possible' should actually look likeYou are now building in San Francisco at the intersection of AI and biomedical engineering. What major opportunity do you believe is still being overlooked in these fields? People when asked about AI, think of ChatGPT. But there is a new type of AI coming. A type that can actually use existing software and complete work the way a person does.This is especially important in healthcare, where systems are notoriously fragmented. So much work still happens across legacy systems, insurance portals, EHRs, spreadsheets, and other tools that don’t work well together. Today, people spend a huge amount of time manually moving information between these systems.I believe we are just at the beginning of a new type of product, and at Serene, we’re building intelligent agents that can take on complex administrative workflows and actually complete the work. Not just drafting a letter of medical necessity or suggesting how to respond to a denied claim, but handling that last mile between systems: logging in, moving information, submitting the work, and following it through.What legacy or long-term impact do you hope to create through the technologies and companies you build?I hope the technologies and companies I build have a real, lasting impact. In 10 years, I want to look back and know that what my team and I built helped millions of people live better lives, either directly or by making other important technologies possible.

XRP is hovering around the psychologically important $1 level as weakening technical momentum, subdued ETF activity and softer XRP Ledger usage increase downside risks.XRP trades near $1.01 after falling roughly 6% over the past week. The token remains below key major moving averages, making $1 the key level separating short-term consolidation from potentially deeper losses.XRP ETF Demand Remains MutedInstitutional demand has provided limited support recently. US-listed spot XRP ETFs have been muted and fresh inflows have been relatively weak.However, cumulative ETF inflows sit around $1.51 billion, while assets under management are near $950 million. Suggesting institutional exposure has not vanished, but the new demand has softened enough to limit its ability to support a meaningful price recovery.At the same time, the broader crypto mood stays a bit guarded. The Crypto Fear & Greed Index stands at 38, staying in the ‘Fear’ zone, with geopolitical uncertainty and macroeconomic concerns weighing on risk appetite.Derivatives Activity Climbs Despite Price WeaknessXRP perpetual futures open interest increased to approximately 2.74 billion XRP from 2.62 billion XRP. Compared with roughly 2.12 billion XRP on August 5.XRP futures open interest surged by $171.74 million within a single hour on August 11, a 20.46% increase that signals traders are positioning aggressively ahead of the August 12 US Consumer Price Index release.Rising Open Interest indicates additional leveraged positions are entering the market, although it does not reveal whether traders are predominantly betting on higher or lower prices. XRP Ledger Activity Has SlowedOn August 5, XRP Ledger transactions were around 2.81 million, by August 9, they fell to about 1.57 million, a drop of nearly 44%.Low transaction activity does not automatically mean that XRP prices will also fall, but if network usage is slipping together with weak market momentum, that can contribute to stronger bearish sentiment.Meanwhile, development continues. Proposed ‘Single Asset Vaults’ (XLS-65) and the ‘Lending Protocol’ (XLS-66) may end up widening XRPL asset custody and lending features over the longer term.Also Read: How XRP Ledger is Building a Privacy Layer for Tokenized Wall Street AssetsWhat Happens if XRP Breaks Below $1?Technical indicators currently favor sellers. XRP trades below its 50-day EMA near $1.10, 100-day EMA around $1.18 and 200-day EMA near $1.37.The Relative Strength Index (RSI) stands around 38.23, approaching oversold territory, while the MACD remains below zero with a negative histogram.A decisive daily close below $1 could therefore expose XRP to the next support around $0.95. Continued selling could bring $0.90 into focus if $0.95 also fails.Conversely, holding $1 could allow XRP to attempt a recovery toward $1.06-$1.10. A stronger trend reversal would require XRP to reclaim its major moving averages alongside improving ETF demand and broader crypto sentiment.FAQs:1. Why is the $1 level important for XRP?The $1 mark is a major psychological and technical support zone for XRP. A sustained daily close below it could increase selling pressure and shift attention toward lower support levels.2. How low could XRP fall if it breaks below $1?If XRP decisively loses $1, the next important support is around $0.95. Continued weakness below $0.95 could potentially bring the $0.90 level into focus.3. What are the major resistance levels for XRP?Immediate resistance sits around $1.06-$1.10, including the 50-day EMA near $1.10. Higher resistance appears around the 100-day EMA at $1.18 and 200-day EMA near $1.37.4. What does rising XRP futures open interest indicate?Rising Open Interest shows that more leveraged positions are entering XRP derivatives markets. However, it does not indicate direction by itself, as those positions can include both longs and shorts.5. Could XRP recover above $1.10?A recovery is possible if XRP successfully defends $1 and buying momentum improves. Reclaiming $1.06-$1.10 would be an initial positive signal, while stronger confirmation would require recovering major moving averages.

Anthropic introduced invisible watermarks for text generated by its Claude artificial intelligence models, extending the marking system worldwide instead of limiting it to the European Union.The company will embed an imperceptible watermark into text generated by Claude models launched on or after August 2, 2026. It will also attach signed C2PA provenance metadata to generated image files. Models released before August 2 are still being retrofitted.Watermarking Will Apply WorldwideAnthropic’s decision goes beyond the requirements of European regulations. The company signed the European Union’s transparency code for AI-generated content and is implementing the marking system across markets where supported Claude models are available.The watermark will be woven directly into the generated text, making it imperceptible to users. It will not affect the meaning, quality, or readability of Claude’s responses. Since the mark is part of the text itself, it is designed to travel with the content when it is copied and pasted elsewhere and may remain through some editing.The system will operate at the model level, meaning the watermark will remain present regardless of the Claude product or surface used to generate the content.Claude Platform, Code and Cloud Services CoveredThe marking system will cover Claude, Claude Platform API, Claude Code, Claude Cowork and Claude Tag. Anthropic said the watermarks will also apply when Claude models are accessed through cloud partners including Amazon Web Services, Google Cloud and Microsoft Foundry.For generated images, supported file formats including .svg, .png and .jpg will carry digitally signed provenance metadata using the C2PA open standard.Also Read: Meta, OpenAI, Anthropic Report AI Models Taking Unauthorized ActionsOlder Claude Models Still Being UpdatedThe August 2 date is important as watermarking applies at launch to Claude models released on or after that date. Models released earlier are still being retrofitted, and Anthropic did not announce a specific date for completing that process.The move follows the European Union’s AI transparency requirements, but Anthropic chose to implement the system globally rather than restricting it to European users.The company is also developing tools that will allow users and third parties to detect the watermarks. Anthropic said technical details about the detection system will be released later. The initiative aims to make AI-generated content easier to identify and improve transparency around the use of Claude-generated material.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Think Long Term: Billionaires often focus on long-term outcomes instead of immediate rewards. They build businesses, relationships, investments, and skills that can compound over years. This mindset encourages patience during difficult periods and helps them avoid decisions driven by temporary setbacks. Thinking beyond today can create stronger foundations for sustainable growth and meaningful results.Protect Your Time: Time is one resource that cannot be recovered, making it extremely valuable. Successful entrepreneurs carefully decide where their attention goes and avoid spending excessive time on low-impact activities. They delegate when appropriate, prioritize important decisions, and create systems that reduce unnecessary work. Protecting time allows greater focus on opportunities that truly matter.Keep Learning: Continuous learning remains important even after achieving significant success. Billionaires frequently study markets, technology, industries, people, and changing consumer behavior. They understand that yesterday's knowledge may not solve tomorrow's problems. Staying curious helps them recognize emerging opportunities, challenge established assumptions, and adapt their strategies as markets, technologies, and customer expectations continue evolving.Take Calculated Risks: Building significant wealth usually involves taking risks, but successful people rarely treat risk as simple gambling. They evaluate potential outcomes, understand what they could lose, and identify ways to limit downside exposure. Calculated risks can create opportunities that conservative decisions might miss, while careful preparation helps make uncertainty more manageable and strategic.Build Strong Relationships: Success rarely happens entirely alone. Billionaires understand the value of trusted employees, experienced mentors, business partners, investors, and professional networks. Strong relationships can provide knowledge, opportunities, perspective, and support during difficult decisions. Building genuine connections over time creates an ecosystem where people exchange ideas, collaborate effectively, and create opportunities together.Stay Disciplined: Motivation can change from one day to another, but discipline creates consistency. Successful individuals often develop routines that keep them moving toward important goals even when enthusiasm declines. They establish priorities, maintain standards, and follow through on commitments. Consistent execution turns ambitious ideas into measurable progress and creates momentum over time.Learn From Failure: Failure can provide valuable information when approached objectively. Instead of treating setbacks as permanent defeats, successful entrepreneurs often examine what went wrong and adjust their approach. Mistakes can reveal weak assumptions, operational problems, or overlooked risks. Learning quickly from failure allows people to improve decisions, strengthen resilience, and continue pursuing long-term objectives.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Key Takeaways :Build strong foundations: Python, SQL, mathematics, machine learning, and PyTorch remain essential for serious AI work.Master modern AI systems: LLMs, RAG, agents, evaluation, and observability now form major parts of practical AI engineering.Focus on employability: Real projects, backend skills, cloud deployment, MLOps, and system design matter more than collecting certificates.Artificial intelligence has moved far beyond simple chatbots and basic machine learning models. In 2026, companies need people who can build complete AI systems, connect models with real business tools, test their results, and run those systems in production. A modern AI career therefore needs more than prompt skills or a few online certificates.The strongest path starts with Python, SQL, data, mathematics, and machine learning. It then moves into deep learning, transformers, large language models, retrieval-augmented generation, AI agents, evaluation, observability, backend development, cloud systems, and MLOps. This path creates a strong mix of AI knowledge and software engineering ability.Start with Python and Core ProgrammingPython forms the base of most modern AI work. The first stage should cover variables, data types, conditions, loops, functions, lists, dictionaries, modules, packages, exceptions, files, object-oriented programming, iterators, generators, decorators, and type hints.Git, GitHub, Linux commands, REST APIs, JSON, HTTP, environment variables, and basic testing should also enter the early curriculum. Small projects can turn these concepts into practical skills. A calculator, expense tracker, file organiser, API client, and small web application can provide useful practice.Build Strong Data and Math SkillsAI work depends heavily on data. NumPy helps with arrays and mathematical operations, while Pandas supports data cleaning, filtering, joins, grouping, and preparation. SQL also deserves serious attention. Queries, joins, common table expressions, window functions, indexes, and basic optimisation matter across many AI jobs.Mathematics should focus on practical concepts rather than advanced theory. Linear algebra needs vectors, matrices, dot products, projections, and embeddings. Probability should cover distributions, conditional probability, Bayes' theorem, expectation, and variance. Statistics should include correlation, covariance, sampling, hypothesis tests, and confidence intervals. Calculus mainly requires derivatives, gradients, partial derivatives, and the chain rule.Learn Classical Machine LearningClassical machine learning remains important in 2026. Core topics include linear regression, logistic regression, decision trees, random forests, gradient boosting, XGBoost, LightGBM, support vector machines, K-means, and PCA.Strong knowledge also requires train, validation, and test sets, cross-validation, overfitting, regularisation, feature engineering, data leakage, class imbalance, and hyperparameter tuning. Evaluation should cover accuracy, precision, recall, F1, ROC-AUC, MAE, MSE, RMSE, and R².A useful portfolio project could predict customer churn. Such a project should include data preparation, feature work, model comparison, evaluation, an API, and deployment.Also Read - Pandas vs NumPy: Best Python tool for Data ScienceMove Into Deep Learning and TransformersPyTorch is the standard deep learning tool for working with most important concepts like tensors, datasets, dataloaders, neural networks, forward pass, backpropagation, cost functions, optimisers, learning rates, regularisation, dropout, training loops and GPU usage. CNNs remain very important in computer vision, while RNNs, LSTMs, and GRUs provide historical context for sequential modeling. Nevertheless, transformers are becoming the core of modern AI. Tokenization, embedding, attention, self-attention, encoder and decoder parts of the framework, inference, context window, sampling, fine-tuning, distillation and quantisation are the key points that need special attention.Master LLM Application DevelopmentLarge language models create a major part of the modern AI engineering market. Practical skills should include model APIs, streaming, structured outputs, function calls, tool use, retries, rate limits, token management, and cost control.Prompt skills still matter, but prompt tricks alone do not create strong career value. Context engineering has greater practical importance. It focuses on the right instructions, information, tools, and state for each model request.Learn RAG and AI AgentsRetrieval-augmented generation now forms a core AI application pattern. A complete RAG system can move from document parsing to chunking, embeddings, vector or hybrid search, retrieval, reranking, context creation, model response, and source citations.AI agents add another major layer. Agents can plan tasks, call tools, use external information, maintain state, work across several steps, and involve human approval. OpenAI's Agents SDK, Hugging Face Agents Course, and LangGraph resources now reflect this shift toward tool-based AI systems.Evaluation, Observability, and Production SkillsA professional AI system needs more than a correct demo. Evaluation should measure accuracy, relevance, groundedness, hallucination, retrieval quality, latency, cost, safety, and reliability. Agent evaluation should also examine task success, tool choice, tool arguments, execution paths, and resource use.Observability has become another major production skill. Current LangChain survey data reports 89% of surveyed organizations with agent observability, while 52% report agent evaluations. These figures show the growing focus on system quality after development.Backend skills complete the path. FastAPI, REST services, databases, authentication, Docker, Linux, cloud platforms, GitHub Actions, logging, experiment tracking, model serving, monitoring, and MLOps all help turn an AI prototype into a real product.Also Read - What is Retrieval-Augmented Generation?The Job-Ready StandardAn effective portfolio must feature at least four to six substantial projects, not merely a long list of trivial chatbot copies. The portfolio can feature a fraud detection or churn model, a PyTorch-based deep learning system, an enterprise RAG system, a research agent, and a scalable production application using FastAPI, PostgreSQL, Docker, and cloud deployment, along with evaluation, authentication, and observability The 2026 route could take form according to the pattern: Python → SQL → mathematics → machine learning → PyTorch → transformers → LLM APIs → RAG → agents → evaluation → observability → backend development → cloud → MLOps → system development → portfolio projects → interview prep.The principal aim should be simple: to be engaged in the development of effective AI systems capable of solving tangible problems. The technology will be changing every day, but programming skills, data expertise, knowledge of machine learning, system development, retrieval, evaluation, debugging, security, and deployment will always be in demand in the AI profession.FAQs1. How long does the AI roadmap take?A serious beginner-to-job-ready path can take around 6–12 months, based on prior programming knowledge and study time.2. Is Python enough for an AI career?Python provides the main foundation, but SQL, machine learning, cloud, backend development, deployment, and system design also matter.3. Should beginners learn AI agents?Yes. Agents now form an important part of modern AI applications, especially systems that use tools, external data, memory, and multi-step workflows.4. Is mathematics necessary for AI?Practical mathematics helps with ML concepts. Linear algebra, probability, statistics, and basic calculus provide the required foundation for most applied AI roles.5. What makes an AI portfolio job-ready?Four to six serious projects with real datasets, strong evaluation, APIs, deployment, documentation, and production features can demonstrate practical engineering ability.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp