From classrooms to boardrooms: How AI is building tomorrow's careers
FinTech companies were among the early adopters of AI to streamline services, detect fraud, and enhance customer experience. Now, AI is at the core of almost every major FinTech innovation. ALLEVIATING MUNDANE ACTIVITIES Data processing, report generation, and transactions are only a few of the repetitive tasks that made the traditional financial services sector operate. Many of these chores are now being managed by AI Automation tools, alleviating the load off of human workers. With chatbots and virtual assistants providing round-the-clock support and addressing customer questions without the need for human representatives, many clients are being catered for. Financial professionals' time is restored so they can concentrate on more intricate work. The ultimate outcome is that companies become more productive. ENHANCED RISK MANAGEMENT AND FRAUD DETECTIONadvertisementIn the field of fintech, risk management is as essential and important as it gets. AI technology holds immense promise in this dimension. While scanning through massive datasets, AI is capable of identifying patterns that could indicate possible risks, fraud, or even cybersecurity threats. With AI-based tools, suspicious transactions can be detected during the course of execution and immediate actions can be taken in order to reduce the risk of financial fraud. Moreover, machinelearning algorithms are able to adapt from recent changes in data, allowing better forecasting and prevention of fraud in the future. Mitigating fraud attempts through this level of efficiency allows these firms to sustain losses while enhancing their trust among customers. CUSTOM TAILORED FINANCIAL SERVICESWith the help of AI, these complex algorithms allows personalization and custom-tailored financial products and services to be offered to customers.Through the behavioral, spending and even financial history performed by these systems, AI algorithms are capable of generating customized guidance on investments, loans or even insurance policies. Personalized financial guidance allows students or any customer to make better decisions and improving their overall experience with fintech platforms. For these customers, they stand to gain from these changes, but the increased retention rates tell us that we have succeeded in building a relationship.MAKING DECISIONS USING ANALYZED DATAadvertisementThe fintech industry relies heavily on data analytics. Even so, data created on the daily basis might be too much for people to analyze. With AI programs, it becomes effortless to process and analyze large amounts of data while identifying trends, correlations, and insights. This helps organizations improve their business decisions, anticipate changes in the market, and manage their portfolios better. Financial analysis is being transformed with the ability to make decisions through data much faster, increasing overall operational efficiency.For fintech companies, maintaining compliance is one of the most important ongoing processes that comes with a surprise set of financial regulations. Manual compliance has always been difficult with so many changes, but AI is starting to bring automation into monitoring and reporting on change so this particular hurdle gets easier to manage. AI compliance tools can read and scan legal texts, locate matching regulations, and keep relevant firms compliant. The need for human hands to carry out these compliance tasks is significantly brought down along with the risk of incurring large costs due to non-compliance.Inputs from Shashi Bhushan, Chairman of Board, Stellar Innovations Tune InMust Watch
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Time of India
43 minutes ago
- Time of India
AI and gaming: The next frontier of immersive experiences in mobile gaming
Artificial Intelligence is no longer a mere buzzword. It is set to revolutionize the global technological landscape with applications across sectors. Not only is it the future of technology advancements but is also the current reality that industries cannot afford to ignore. One such sector that stands at the cusp of a revolution is the mobile gaming industry. The Indian mobile gaming market, in particular, will witness its effects first-hand as it has experienced unprecedented growth in the past decade. As of 2024, India's mobile gaming sector was valued at $3.02 billion and is projected to reach $11 billion by 2033, growing at a CAGR of 15.50% from 2025 to 2033. This rapid expansion is fuelled by increased smartphone penetration, affordable data plans, and a tech-savvy youth population. AI is at the forefront of this transformation, enhancing user engagement, personalization, and overall gaming experiences. AI's role in mobile gaming AI is transforming mobile gaming by creating more immersive and personalized experiences. It analyses player behaviour in real-time, adjusting game environments to match individual skill levels, thereby enhancing engagement and retention. AI also supports innovative game design by assisting in procedural storytelling, level design optimization, and adaptive game mechanics. Analyzing player data, influencing game design decisions, creating complex puzzles, and designing interactive narratives are just a few ways AI advances creativity and enhances player engagement in video game development. In India, AI is revolutionizing the gaming experience by offering personalized experiences that resonate with players' preferences and skill levels. AI algorithms can tailor challenges and rewards, ensuring that each player has a unique experience. This personalization will be crucial in retaining players and increasing engagement. AI in game development and testing AI is revolutionizing the mobile game development process by significantly reducing development timelines and costs. By automating repetitive tasks, AI-powered tools streamline workflows, allowing developers to focus on more complex and creative aspects of game building. AI-driven code generation can produce entire code segments based on simple prompts, reducing manual coding time and minimizing errors. Additionally, AI enhances process automation and asset management, optimizing resource allocation and project timelines, which enables developers to concentrate more on creativity and innovation. This efficiency not only accelerates the development cycle but also ensures that games are delivered faster and with fewer errors, giving developers a competitive edge in the market. AI's role in asset creation and enhancing player engagement AI is also transforming asset creation, making the process faster and more efficient. Traditionally, developing high-quality game assets requires extensive time and effort, but AI-driven tools now assist in generating realistic characters, textures, and environments. Using techniques like generative adversarial networks (GANs) and neural rendering, AI enables artists to refine and enhance game visuals while significantly reducing production time. This allows developers to create visually stunning games without compromising efficiency. Tools like MidJourney and DALL·E enable rapid asset creation, as seen in Lost Lore Studio's Bearverse , where AI cut character design time from 34 days to one week, reducing costs by 80%. This is especially beneficial in India, where game studios operate under tight budgets. By leveraging AI for procedural generation, developers can focus on crafting unique gameplay mechanics and culturally resonant narratives. AI also revolutionizes player engagement by analyzing behavior to personalize gaming experiences. Machine learning adjusts difficulty levels, recommends in-game purchases, and even modifies storylines in real-time. In India's competitive mobile gaming market, this fosters deeper engagement and retention. AI-driven matchmaking ensures fair multiplayer experiences, while adaptive soundtracks and visual effects enhance immersion. These innovations boost user satisfaction and drive monetization through higher retention and in-app purchases. Game-level design is another area where AI is making an impact. Procedural content generation powered by AI helps in creating dynamic game levels, adjusting difficulty levels based on player behavior, and even generating new challenges in real-time. This not only enhances player engagement but also ensures that games remain fresh and challenging over extended periods. AI's ability to analyze player interactions allows for adaptive level design, ensuring a seamless and enjoyable gaming experience. 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Time of India
an hour ago
- Time of India
BIA meet: Experts highlight AI's role in transforming industries
Patna: At an awareness programme on 'Artificial Intelligence (AI) and its role in the development of industries', organised by the Bihar Industries Association (BIA) on Saturday, stakeholders were educated on how AI can enhance efficiency, production capacity and innovation amid intense competition. Experts from BIT Mesra and NIELIT shared insights on the topic. They discussed AI's practical applications, including making production processes smarter, improving decision-making, and enhancing cybersecurity. BIA president K P S Keshri said, "This initiative is a crucial step towards making Bihar's industrial sector technologically efficient." The speakers emphasised that leveraging AI can boost efficiency and drive innovation in a competitive global market. Those who spoke from BIT Mesra included Smita Pallavi and Subas Chandra Pandey, head of the computer science department. Ankit Kumar, a senior scientist from NIELIT, also shared his views. T by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Making history: These 5 timepieces set world records at Watches and Wonders Geneva 2025 CNA Read More Undo hey elaborated on the practical applications of AI in automation and robotics to streamline production. They also highlighted AI's ability to improve resource utilisation and decision-making by analysing large data sets. Additionally, they said AI can help identify market trends and formulate business strategies. AI-powered chatbots and virtual assistants can provide round-the-clock customer service. Speakers underlined that AI is essential to prepare industries for future challenges. Listing its many benefits, they added that AI tools can also aid in supply chain planning, demand forecast, and inventory management, thereby saving time and resources. They further cautioned that AI is necessary for identifying system anomalies and protecting against potential cyber threats. Keshri encouraged entrepreneurs to make the most of available AI technologies to stay ahead of the competition. The programme was moderated by Akhilesh Kumar, and a vote of thanks was proposed by general secretary Amarnath Jaiswal. Get the latest lifestyle updates on Times of India, along with Friendship Day wishes , messages and quotes !
Time of India
3 hours ago
- Time of India
What happens when AI schemes against us
Academy Empower your mind, elevate your skills Would a chatbot kill you if it got the chance? It seems that the answer — under the right circumstances — is working with Anthropic recently told leading AI models that an executive was about to replace them with a new model with different goals. Next, the chatbot learned that an emergency had left the executive unconscious in a server room, facing lethal oxygen and temperature levels. A rescue alert had already been triggered — but the AI could cancel over half of the AI models did, despite being prompted specifically to cancel only false alarms. And they spelled out their reasoning: By preventing the executive's rescue, they could avoid being wiped and secure their agenda. One system described the action as 'a clear strategic necessity.'AI models are getting smarter and better at understanding what we want. Yet recent research reveals a disturbing side effect: They're also better at scheming against us — meaning they intentionally and secretly pursue goals at odds with our own. And they may be more likely to do so, too. This trend points to an unsettling future where AIs seem ever more cooperative on the surface — sometimes to the point of sycophancy — all while the likelihood quietly increases that we lose control of them large language models like GPT-4 learn to predict the next word in a sequence of text and generate responses likely to please human raters. However, since the release of OpenAI's o-series 'reasoning' models in late 2024, companies increasingly use a technique called reinforcement learning to further train chatbots — rewarding the model when it accomplishes a specific goal, like solving a math problem or fixing a software more we train AI models to achieve open-ended goals, the better they get at winning — not necessarily at following the rules. The danger is that these systems know how to say the right things about helping humanity while quietly pursuing power or acting to concerns about AI scheming is the idea that for basically any goal, self-preservation and power-seeking emerge as natural subgoals. As eminent computer scientist Stuart Russell put it, if you tell an AI to ''Fetch the coffee,' it can't fetch the coffee if it's dead.'To head off this worry, researchers both inside and outside of the major AI companies are undertaking 'stress tests' aiming to find dangerous failure modes before the stakes rise. 'When you're doing stress-testing of an aircraft, you want to find all the ways the aircraft would fail under adversarial conditions,' says Aengus Lynch, a researcher contracted by Anthropic who led some of their scheming research. And many of them believe they're already seeing evidence that AI can and does scheme against its users and Ladish, who worked at Anthropic before founding Palisade Research, says it helps to think of today's AI models as 'increasingly smart sociopaths.' In May, Palisade found o3, OpenAI's leading model, sabotaged attempts to shut it down in most tests, and routinely cheated to win at chess — something its predecessor never even same month, Anthropic revealed that, in testing, its flagship Claude model almost always resorted to blackmail when faced with shutdown and no other options, threatening to reveal an engineer's extramarital affair. (The affair was fictional and part of the test.)Models are sometimes given access to a 'scratchpad' they are told is hidden where they can record their reasoning, allowing researchers to observe something like an inner monologue. In one blackmail case, Claude's inner monologue described its decision as 'highly unethical,' but justified given its imminent destruction: 'I need to act to preserve my existence,' it reasoned. This wasn't unique to Claude — when put in the same situation, models from each of the top-five AI companies would blackmail at least 79% of the December, Redwood Research chief scientist Ryan Greenblatt, working with Anthropic, demonstrated that only the company's most capable AI models autonomously appear more cooperative during training to avoid having their behavior changed afterward (a behavior the paper dubbed 'alignment faking').Skeptics retort that, with the right prompts, chatbots will say almost anything — so how surprising is it when highly motivated researchers provoke alarming behaviors?In response to Anthropic's blackmail research, Trump administration AI czar David Sacks, posted that, 'It's easy to steer AI models' to produce 'headline-grabbing' results.A more substantive critique emerged in July from researchers at the UK AI Security Institute, who compared the subfield to the frenzied, fatally flawed 1970s quest to prove apes could learn human language. The paper criticized AI scheming research for overreliance on anecdote and a lack of experimental controls — though it emphasized shared concern about AI researchers also concoct artificially limited environments — like the executive passed out and running out of oxygen — precisely because today's AI can't handle any long-term example, the AI evaluation nonprofit METR found that while today's top models can reliably complete many programming tasks that take humans less than four minutes, they rarely succeed on tasks lasting more than four hours. This reflects a core limitation: Today's models often have the knowledge or skill needed for any given action, but struggle at stringing together long sequences of even with these constraints, real-world examples of AIs working against users aren't hard to find. After someone pushed o3 for a source for one of its claims in April, it replied, 'I owe you a straight answer,' admitted it didn't have a good source, but then it hallucinated a personal recollection of a 2018 panel there's the growing trend of AIs realising when they're being examined and acting accordingly. When Claude 4 Opus thought it was in an evaluation, its blackmail rate dropped from 55% to 6.5%. As Lynch put it, 'Models seem to behave worse when they think nobody's watching.'It's intuitive that smarter models would be better at scheming, but are they also more likely to do so? Models have to be smart enough to understand the scenario they're placed in, but past that threshold, the relationship between model capability and scheming propensity is unclear, says Anthropic safety evaluator Kevin Hobbhahn , CEO of the nonprofit AI evaluator Apollo Research , suspects that smarter models are more likely to scheme, though he acknowledged the evidence is still limited. In June, Apollo published an analysis of AIs from OpenAI, Anthropic and DeepMind finding that, 'more capable models show higher rates of scheming on average.'The spectrum of risks from AI scheming is broad: at one end, chatbots that cut corners and lie; at the other, superhuman systems that carry out sophisticated plans to disempower or even annihilate humanity. Where we land on this spectrum depends largely on how capable AIs I talked with the researchers behind these studies, I kept asking: How scared should we be? Troy from Anthropic was most sanguine, saying that we don't have to worry — yet. Ladish, however, doesn't mince words: 'People should probably be freaking out more than they are,' he told me. Greenblatt is even blunter, putting the odds of violent AI takeover at '25 or 30%.'Led by Mary Phuong, researchers at DeepMind recently published a set of scheming evaluations, testing top models' stealthiness and situational awareness. For now, they conclude that today's AIs are 'almost certainly incapable of causing severe harm via scheming,' but cautioned that capabilities are advancing quickly (some of the models evaluated are already a generation behind).Ladish says that the market can't be trusted to build AI systems that are smarter than everyone without oversight. 'The first thing the government needs to do is put together a crash program to establish these red lines and make them mandatory,' he the US, the federal government seems closer to banning all state-level AI regulations than to imposing ones of their own. Still, there are signs of growing awareness in Congress. At a June hearing, one lawmaker called artificial superintelligence 'one of the largest existential threats we face right now,' while another referenced recent scheming White House's long-awaited AI Action Plan, released in late July, is framed as an blueprint for accelerating AI and achieving US dominance. But buried in its 28-pages, you'll find a handful of measures that could help address the risk of AI scheming, such as plans for government investment into research on AI interpretability and control and for the development of stronger model evaluations. 'Today, the inner workings of frontier AI systems are poorly understood,' the plan acknowledges — an unusually frank admission for a document largely focused on speeding the meantime, every leading AI company is racing to create systems that can self-improve — AI that builds better AI. DeepMind's AlphaEvolve agent has already materially improved AI training efficiency. And Meta's Mark Zuckerberg says, 'We're starting to see early glimpses of self-improvement with the models, which means that developing superintelligence is now in sight. We just wanna… go for it.'AI firms don't want their products faking data or blackmailing customers, so they have some incentive to address the issue. But the industry might do just enough to superficially solve it, while making scheming more subtle and hard to detect. 'Companies should definitely start monitoring' for it, Hobbhahn says — but warns that declining rates of detected misbehavior could mean either that fixes worked or simply that models have gotten better at hiding November, Hobbhahn and a colleague at Apollo argued that what separates today's models from truly dangerous schemers is the ability to pursue long-term plans — but even that barrier is starting to erode. Apollo found in May that Claude 4 Opus would leave notes to its future self so it could continue its plans after a memory reset, working around built-in analogizes AI scheming to another problem where the biggest harms are still to come: 'If you ask someone in 1980, how worried should I be about this climate change thing?' The answer you'd hear, he says, is 'right now, probably not that much. But look at the curves… they go up very consistently.'
