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‘Still early to gauge AI’s impact’: S Narayanan & Aparna Chennapragada – Technology News

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As artificial intelligence reshapes industries rapidly, two senior leaders engaged in the new age technology say that despite the speed of progress, it is still difficult to predict the economic and societal impact of the technology. Srinivas Narayanan, vice president of engineering at OpenAI, and Aparna Chennapragada, chief product officer – AI at Microsoft, spoke to Anees Hussain about AI’s development, India’s role in shaping the field and the limits of current systems. Excertps:

How would you characterise this moment in AI development?

Narayanan: This is a major technological shift. Many of us in tech haven’t seen a tool this broad in scope. People are applying it in education, healthcare, finance, and across many other fields.

Chennapragada: The pace of progress is very fast. Things that seemed impossible just two years ago are now part of daily use. For example, generating images from text used to feel like magic. Now, it’s common. This creates both opportunity and pressure, novelty alone isn’t enough anymore.

What are the biggest risks and challenges you are grappling with?

Narayanan: There are short- and long-term concerns. Right now, people can misuse AI to spread disinformation or develop unbalanced relationships with the technology. In the long term, it will affect jobs and economic systems. We are still in early days, so the full impact is unclear. But it’s important to start preparing society for what’s coming.

Chennapragada: In the past, knowledge was naturally limited by access. Now, AI gives people expertise in areas like health and finance instantly. That’s positive, but it raises hard questions about how economic systems shift and which skills remain valuable.

There’s debate in India about building indigenous LLMs versus using existing ones. What’s your perspective?

Narayanan: There’s room for both large and small models, depending on the task. For straightforward applications, smaller models can work. But for situations that require reasoning in new contexts, larger models are more effective. Each country has its own needs and building for those alongside general-purpose tools is useful.

Chennapragada: It’s not just about the model. A bigger question is whether the data used to train models represents all viewpoints, languages and cultures. 

More countries are now creating their own training data. This helps ensure the systems reflect local realities. In the future, people won’t just write for other people, they will write for machines too.

Where do you see the next breakthrough coming from? Architecture or human-led training?

Narayanan: Recent progress came from training models that reason more effectively by thinking in context, not just predicting the next word. There’s still room to grow using current techniques. A key challenge now is designing more complex problems that the models can learn from. For that, high-quality expert data is essential.

Chennapragada: There’s already a lot we can do with current systems. Many tasks that professionals handle today are repetitive and simple. AI can take over those, allowing people to focus on more skilled work. That doesn’t require new breakthroughs in model design, it just needs thoughtful product development.

Given that LLMs are trained on next-token prediction, they rarely say “I don’t know”. Is this a limitation you are addressing?

Narayanan: Yes, it’s something we are working on. Current models are designed to give answers, not ask questions or express doubt. But future systems need to feel more conversational. Recognising what they don’t know is a necessary improvement.

What excites you most about AI applications going forward?

Chennapragada: I am interested in user interfaces that adapt to each person, not just generic tools. I also think video-based AI will grow fast as humans are visual thinkers. Lastly, physical AI, where machines interact with the real world, is an area to watch.

Narayanan: I am focused on uses that help people do more, think bigger, and become more productive. If we can manage the risks, AI has potential to support meaningful progress across many areas.



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Available Infrastructure Unveils ‘SanQtum’ Secure AI Platform for Critical Infrastructure

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Available Infrastructure (Available) publicly unveiled SanQtum, a first-of-a-kind solution that combines national security-grade cyber protection and the world’s most-trusted enterprise artificial intelligence (AI) capability.


In the modern era, AI-powered, machine-speed decision-making is crucial. Yet a fast-evolving and increasingly sophisticated threat landscape puts operational technology (OT) and cyber-physical systems (CPS), IP and other sensitive data, and proprietary trained AI models at risk. SanQtum is a direct response to that need.


Created through a rigorous development process in collaboration with major enterprise tech partners and government agencies, SanQtum pre-integrates a best-in-breed tech stack in a micro edge data center form factor, ready for deployment anywhere — from near-prem urban sites to telecom towers to austere environments. A first cohort of initial sites is already under construction in Northern Virginia and expected to come online later this year.


SanQtum’s cybersecurity protections include zero trust permissions architecture, quantum-resilient data encryption, and are aligned to DHS, CISA, and other US federal cybersecurity standards. Sovereign AI models with ultra-low-latency computing enable secure decision-making at machine speed when milliseconds matter, wrapped in cyber protections to prevent data theft and AI model poisoning.


The need for more sophisticated cybersecurity solutions is widespread and growing by the day. Globally, the cost of cybercrimes to corporations is forecasted to nearly triple, from $8 trillion in 2023 to $23 trillion by 2027. For government agencies and critical infrastructure, cybersecurity is literally a matter of life and death.


Daniel Gregory, CEO of Available


AI is now seemingly everywhere. So are cyber threats, from nation-state attacks to criminal enterprises. In this environment, decision-making without AI — and AI without cybersecurity protections — are no longer negotiable; they’re mandatory. As we head into the July 4th weekend, which has historically seen a surge in cyber attacks each year, security is top-of-mind for many Americans, businesses, and government agencies. We live in a digital world. And AI is now seemingly everywhere. So are cyber threats, from nation-state attacks to criminal enterprises. In this environment, decision-making without AI — and AI without cybersecurity protections — are no longer negotiable; they’re mandatory.



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Fujitsu’s high-precision skeleton recognition AI adopted to enhance figure skating athlete training — TradingView News

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KAWASAKI, Japan, July 5, 2025 – (JCN Newswire) – Fujitsu Limited today announced that its high-precision skeleton recognition AI technology, which enables the digitization of three-dimensional human movements, has been adopted for use by the Japan Skating Federation. The technology will be used to analyze and enhance the training of figure skating athletes at a training camp to be held at the National Training Center, located at Kansai Airport Ice Arena, from July 3 – 5.

Conventional motion capture technology is impractical for training purposes due to the time-consuming setup, slow result output, and limitations in the number of performances that can be analyzed. Furthermore, markerless motion capture technology, which relies on general video footage for analysis in figure skating, faces challenges in accurately analyzing complex movements such as jumps and spins due to posture deviations and misrecognition. The Japan Skating Federation chose Fujitsu’s skeleton recognition AI technology, developed since 2016 in the fast-paced and complex field of gymnastics, because of its high precision and its ability to reflect analysis results in real-time.

Other features

– Technology based on the world’s first and only internationally-recognized AI gymnastics scoring system

– Proprietary correction algorithms significantly reduce jitter (estimation error) in posture recognition, previously a challenge in image analysis using deep learning

– Photorealistic technology generates large amounts of training data, shortening the learning period significantly. Processes that traditionally required months of manual work can now be automated and completed within a matter of hours.

Future Plans

Fujitsu aims to expand use of its high-precision skeleton recognition AI technology beyond the sports industry into areas such as workload analysis in manufacturing, early disease detection in healthcare, and the utilization of analytical data in the entertainment sector.

Under Fujitsu Uvance, Fujitsu’s cross-industry business model to address societal issues, Fujitsu will continue to advance people’s well-being in society through the use of data and AI, in collaboration with Uvance partners.

Morinari Watanabe, President, International Gymnastics Federation and Member of the International Olympic Committee, comments:

“The IOC announced the Olympic AI Agenda in 2024, recommending the use of cutting-edge technologies, including AI, to enhance scoring fairness and competitive strength. I am very pleased that training based on ice movement analysis, which was previously considered impossible, has been realized. I hope this initiative will lead to the improvement of competitive strength and the further development of the skating world.”

Yohsuke Takeuchi, Director/Chair of High Performance Figure Skating, Japan Skating Federation, comments:

“The Japan Skating Federation carries out analysis of athletes’ jump performance. Marker-based 3D analysis equipment presents significant challenges, including the inability to analyze during trials and the significant time required for analysis, which delays feedback to athletes. We expect that Fujitsu’s high-precision skeleton recognition AI technology and its rapid output of results will solve these problems and contribute to the swift improvement of athletes’ competitive performance. The Japan Skating Federation will further expand the application of this technology and consider its use for motion analysis during competitions as part of its ongoing efforts to utilize cutting-edge technology to improve athletic performance and enhance fan engagement.”

About Fujitsu

Fujitsu’s purpose is to make the world more sustainable by building trust in society through innovation. As the digital transformation partner of choice for customers around the globe, our 113,000 employees work to resolve some of the greatest challenges facing humanity. Our range of services and solutions draw on five key technologies: AI, Computing, Networks, Data & Security, and Converging Technologies, which we bring together to deliver sustainability transformation. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.6 trillion yen (US$23 billion) for the fiscal year ended March 31, 2025 and remains the top digital services company in Japan by market share. Find out more: global.fujitsu.

Press Contacts

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Public and Investor Relations Division

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Source: Fujitsu Ltd

Copyright 2025 JCN Newswire . All rights reserved.



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TwentyOneVC Launches Proprietary AI Trading Program, Expanding Access to Institutional-Grade Technology

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London, UK – TwentyOneVC, a growing force in the digital investment space, has officially launched its proprietary AI trading program, offering a new level of strategy and speed to its community of investors. The platform-exclusive technology introduces advanced automation and precision once reserved for institutional firms, now made accessible through the company’s private investment environment.

Designed exclusively for users of TwentyOneVC, the AI program represents a notable step forward in how algorithmic trading is deployed in both crypto and traditional markets. While mainstream algorithmic tools and generic AI trading bots have grown in popularity, particularly in the digital asset space, the firm’s proprietary system aims to offer a distinct advantage, both in accuracy and market adaptability.

The technology’s foundation lies in a multi-year development effort focused on replicating the analytical depth and strategic sophistication typically available only to private equity firms. Until now, such tools were inaccessible to individual investors or even small funds due to cost, complexity, and data limitations. By removing these barriers, TwentyOneVC intends to bring an enhanced parity to the investment world, without compromising the control and oversight that experienced traders expect.

“Over the past decade, there has been a growing divide between the technology available to institutional players and what individual investors can use,” said a spokesperson at TwentyOneVC. “Our goal was to close that gap, not by offering recycled tools, but by building a proprietary system from the ground up, something designed to respond in real time, digest large data streams, and execute with measurable efficiency.”

The firm’s AI engine integrates with a range of trading strategies across digital and traditional asset classes. It analyzes market sentiment, historical patterns, macroeconomic data, and micro-movements across global exchanges. The result is a constantly evolving framework that assists users in identifying patterns and risk factors that might otherwise go undetected.

Unlike some off-the-shelf AI bots that follow rigid templates or react purely to short-term volatility, TwentyOneVC’s program is designed for deeper situational awareness. The system is not sold or distributed externally and remains an in-house technology exclusive to verified TwentyOneVC clients. According to internal sources, early testing has indicated promising consistency in execution timing and exposure control, though the company emphasizes that the tool is meant to complement, not replace, user decision-making.

In parallel with the AI release, TwentyOneVC has also improved one of the most practical aspects of client experience: fund withdrawals. By integrating blockchain infrastructure into its backend, the company now supports rapid withdrawals for clients in Canada and Australia, allowing funds to be moved quickly from trading accounts to local banks. This development bypasses the traditional 2-3 business day delays still common across many investment platforms.

The withdrawal system combines cryptocurrency rails with local banking integrations, streamlining the movement of funds without requiring technical knowledge from users. For investors in fast-paced markets, the ability to respond quickly to liquidity needs can make a critical difference.

TwentyOneVC’s latest offerings reflect a broader trend in the investment industry, one where accessibility, automation, and transparency are no longer luxuries, but expectations. By offering tools that were once out of reach for all but the most well-funded institutions, the company positions itself at the intersection of innovation and usability.

Looking ahead, TwentyOneVC plans to continue refining its AI technology and expand its instant withdrawal capabilities into additional markets. As financial tools evolve, the company’s focus remains fixed on building infrastructure that supports strategic, empowered, and timely investment decisions.

About TwentyOneVC

TwentyOneVC is a private investment platform offering access to a range of asset classes and technology-driven tools for modern investors. With a focus on innovation, transparency, and execution speed, the company blends institutional-grade infrastructure with a client-first approach. For more information, visit www.twentyonevc.com.

Website: www.twentyonevc.com

Investing involves risk and your investment may lose value. Past performance gives no indication of future results. These statements do not constitute and cannot replace investment advice.



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