ConnectingAI #112: Agentic AI Needs Strong Hardware Support and Evaluation and more

Top ConnectingAI articles of the week 

1- Agentic AI Needs Strong Hardware Support and Evaluation: As agentic AI systems become more autonomous, their safe and scalable deployment hinges on robust evaluation frameworks and coordinated hardware. Without this foundation, reliability and control become harder to guarantee.

2- India Prioritizes GPU Infrastructure for Nation-Scale AI: With AI use cases expanding rapidly, India is ramping up investment in data centers and compute power to meet growing GPU demand. AMD is doubling down with plans to grow its workforce in India to over 10,000 in the next few years.

3- EDA Firms Are Leading the AI Hardware Revolution: EDA giants like Cadence, Siemens, and Synopsys are integrating AI into their chip design platforms to enhance performance and reduce development time. Cadence’s goal of “Level 5 autonomy” could cut design cycles by up to 50%.

4- Next-gen AI chips will draw 15,000W each, redefining power and cooling: A new KAIST report warns that by 2035, cutting-edge AI processor modules (with HBM8 memory) could consume over 15 kilowatts each, far beyond today’s server capabilities. Such extreme power draw will push data centers to adopt radically new infrastructure as conventional air-cooling can’t handle the heat of 1,200W GPUs and densely stacked memory

5 - Memory makers double down on AI demand: SK Hynix – a key memory supplier for AI – says it’s on track to double its sales of high-bandwidth memory (HBM) chips this year amid surging demand from new AI model launches. The firm is boosting capital spending on cutting-edge equipment to expand HBM production, betting on sustained growth as cloud customers stockpile chips and rival Samsung races to catch up. 

AI piqued my interest

1 - AI helps Latin scholars decipher ancient Roman texts:  Historians are tapping a new AI tool (nicknamed “Aeneas”) to reconstruct thousands of damaged Latin inscriptions from the Roman Empire. Trained on 170,000+ ancient texts, the generative model can guess missing words, dates, and locations – providing useful starting points that help human scholars interpret and date artifacts that were previously indecipherable.

2 - BBC launches an AI Creative Lab for kids & family content: BBC Studios is opening a dedicated AI Lab to “supercharge” innovation in storytelling and production workflows. The lab will bring together technologists and creatives to experiment with AI in areas from concept development to post-production – exploring new formats and “ways to tell stories that matter” while ensuring transparency and upholding the BBC’s editorial principles.

3 - AI tool predicts cancer aggressiveness from tumor ‘stemness’: Medical researchers have developed a machine-learning model that gauges how aggressive a tumor is by measuring its “stemness” – how closely the cancer cells resemble stem cells. By analyzing specific protein patterns in a tumor, the AI generates a stemness score (0 to 1) that correlates with the cancer’s likely resistance to treatment and risk of recurrence. This could help doctors personalize therapies, and the team has already pinpointed proteins that might be targets for new treatments to improve patient outcomes.

4 - Designing AI for students with disabilities: A new Stanford white paper calls for AI in education to be built “with [students’] needs and voices at the center,” so that learners with disabilities are not overlooked. The report AI + Learning Differences outlines 12 recommendations to ensure AI-powered tools equitably support students with learning differences (like dyslexia or ADHD). By embracing inclusive design – for example, AI that enhances assistive tech or adapts Individualized Education Plans – developers can create learning tools that benefit all students through greater personalization and accessibility.

More on ConnectingAI, Connecting Everything next week

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