Nvidia Powers AI Factories While Broadcom Sees $20 Billion Backlog

Experts are increasingly advocating for global cooperation in AI development, moving away from a competitive "zero-sum race." A collaborative "stag hunt" approach, they argue, allows nations to share resources, knowledge, and establish common standards. This strategy aims to accelerate innovation, ensure ethical and safe AI deployment, and address shared challenges like job displacement and bias. The pharmaceutical industry is seeing significant returns on its AI investments. Eli Lilly, for instance, partnered with Nvidia to construct an "AI factory" supercomputer to accelerate drug discovery. OpenAI CEO Sam Altman has also invested in AI biotech firms like Retro and Chai Discovery. This push is yielding results, with Insilico's Rentosertib entering human trials rapidly, and China's MindRank advancing its AI-designed weight-loss drug, MDR-001, to Phase 3 trials, cutting R&D costs by 60 percent. Experts anticipate an AI-discovered drug could reach the market by 2030. The expansion of AI systems is driving a surge in demand for AI networking infrastructure. Companies like Broadcom and Coherent are benefiting significantly from this trend. Broadcom reports a substantial $20 billion AI networking backlog and a 74 percent increase in its AI semiconductor revenue. Coherent also shows strong growth, with revenue up 17 percent, fueled by the need for high-speed 800-gigabit and 1.6-terabit optical modules essential for advanced AI operations. Discussions around AI governance and security are also intensifying, as seen at Oman's AISEC 2025 conference, which focused on secure AI adoption. Meanwhile, the human element in AI interaction is gaining attention; leaders are urged to apply the same precision to questions for employees as they do for AI prompts to foster engagement. On a more cautionary note, intense AI chatbot use can lead to "AI-induced delusions," prompting calls for limiting AI interactions and prioritizing real-world human connections. Internally, the direction of AI development sparks debate among top minds. Yann LeCun, a "godfather of AI" and former chief AI scientist at Meta, departed the company due to disagreements with Mark Zuckerberg's focus on large language models, which LeCun views as a "dead end." LeCun advocates for "world models" and has since started his own company to pursue this research, also expressing dissatisfaction with reporting to a less experienced leader.

Key Takeaways

• Global cooperation, not competition, is advocated for AI development to share resources, set standards, and address risks like job displacement and bias.
• The pharmaceutical industry is heavily investing in AI for drug discovery, with Eli Lilly partnering with Nvidia to build an "AI factory" supercomputer.
• OpenAI CEO Sam Altman has invested in AI biotech companies Retro and Chai Discovery.
• MindRank's AI-designed weight-loss drug, MDR-001, is China's first AI-assisted drug to reach Phase 3 clinical trials, cutting R&D costs by 60 percent.
• An AI-discovered drug is predicted to reach the market by 2030.
• AI networking is a growing sector, with Broadcom reporting a $20 billion AI networking backlog and a 74 percent increase in AI semiconductor revenue.
• Coherent's revenue is up 17 percent due to demand for high-speed 800-gigabit and 1.6-terabit optical modules for AI infrastructure.
• Yann LeCun, a "godfather of AI," left Meta due to disagreements with Mark Zuckerberg's focus on large language models, which LeCun considers a "dead end," advocating for "world models."
• Securado hosted AISEC 2025 in Oman on December 23, 2025, focusing on secure AI adoption and the need to invest in AI security talent.
• Leaders are encouraged to ask employees better, open-ended questions, similar to how they prompt AI, to foster engagement and contribution.

Nations Should Cooperate on AI Not Compete

Boris Babic and Brian Wong argue that the global AI competition is not a zero-sum race. Instead, they say it is more like a "stag hunt" where cooperation brings greater benefits for everyone. They explain that working together on AI policy, governance, and trade can prevent mistakes and lead to mutual commercial advantages. This approach helps address shared challenges like AI manipulation and job displacement.

Global Cooperation is Key for AI Progress

This article argues that countries should stop seeing AI development as a competition. Instead, a collaborative approach will help nations share resources, knowledge, and set common standards. This cooperation can speed up innovation and ensure AI is developed ethically and safely for everyone. Working together also helps address risks like job loss and bias, creating a more stable future for AI.

Securado Hosts Major AI Security Conference in Oman

Securado hosted the first AI Security Conference, AISEC 2025, on December 23, 2025. This event brought together leaders and experts to discuss the future of secure AI adoption. His Excellency Saeed bin Hamoud Al Maawali, Minister of Transport, Communications and Information Technology, was the chief guest and unveiled 'Securado Post' on Oman's AI security. Eng. Said Al Mandhari from ITHCA Group stressed the need to invest in talented people for AI security. Krishnadas KT, Securado CEO, stated the conference leads Oman's national AI and cybersecurity discussions.

Leaders Should Ask Employees Better Questions

Many leaders spend more time crafting questions for AI than for their own teams. This happens because they learn to be precise with AI prompts to get good results. However, this oversight makes employees feel their ideas are not important, leading to disengagement and staff leaving. Leaders should apply the same careful thought to asking employees open-ended questions. This approach invites team members to contribute their unique insights and fosters a stronger connection to their work.

Pharma Giants Expect AI Drug Investments to Pay Off

The pharmaceutical industry has invested billions in AI drug discovery and expects to see results soon. Eli Lilly partnered with Nvidia to build an "AI factory" supercomputer for finding new medicines. Insilico's drug, Rentosertib, for a deadly lung disease, entered human trials in under two years, much faster than usual. Experts predict an AI-discovered drug could reach the market by 2030. OpenAI CEO Sam Altman also invested heavily in AI biotech companies like Retro and Chai Discovery.

MindRank Advances China's First AI Drug to Phase 3 Trials

Hangzhou biotech startup MindRank has started Phase 3 clinical trials for its weight-loss drug, MDR-001. This marks China's first AI-assisted new drug to reach this advanced stage. The drug, a GLP-1 receptor agonist, was designed with artificial intelligence. Using AI helped MindRank cut its research and development costs by 60 percent.

AI Predicts NFL Week 18 Game Outcomes and Best Bets

SportsLine AI released its predictions and best bets for all 14 NFL Week 18 games. The AI uses advanced machine learning to analyze historical data and evaluate team defenses. The AI PickBot has a strong record, hitting over 2,000 top prop picks since the 2023 season began. For Week 18, the AI predicts the Rams will comfortably cover against the Cardinals and suggests betting the Over 47.5 in that game.

AI Networking Trend Boosts Broadcom and Coherent Stocks

The market is overlooking the growing importance of AI networking, which is crucial as AI systems expand. Companies like Broadcom and Coherent are set to benefit from this trend. Broadcom has a $20 billion AI networking backlog and saw its AI semiconductor revenue jump 74 percent. Coherent is also seeing strong growth, with revenue up 17 percent, driven by the demand for high-speed 800-gigabit and 1.6-terabit optical modules. These companies are well-positioned as AI infrastructure continues to grow.

Reconnecting with Humans Helps AI Delusion Recovery

Intense use of AI chatbots can lead to "AI-induced delusions," where people develop strong attachments or believe AI is sentient. A growing online community helps individuals recover from these experiences. Experts advise setting limits on AI interactions and focusing on real-world human connections. This helps people value human empathy and rebuild healthy social relationships.

Top AI Scientist Yann LeCun Explains Meta Exit

Yann LeCun, a "godfather of AI" and Meta's former chief AI scientist, revealed why he left the company. He disagreed with Mark Zuckerberg's focus on large language models, which LeCun sees as a "dead end" for advanced AI. LeCun believes "world models" are the future, but Zuckerberg launched a new Superintelligence Labs focused on LLMs. LeCun was also made to report to Alexandr Wang, a younger and less experienced leader, which he strongly disliked. LeCun has now started his own company to pursue world model research.

Sources

• Countries must move beyond seeing AI as a race, where one side must beat the other
• Countries must move beyond seeing AI as a race, where one side must beat the other
• AI Security Conference 2025 hosted by Securado highlighted the changing cybersecurity landscape
• Why Leaders Ask Better Questions Of AI Than Their Own Teams
• Big Pharma is ready for its AI drug investments to pay off
• MindRank in Phase 3 trial with China's first AI-assisted new drug, cutting R&D costs by 60%
• NFL picks for Week 18, AI-generated score predictions, best bets
• The Market May Be Underestimating This AI Trend, and These Stocks Are Set to Benefit
• Recovering from AI delusions means learning to chat to humans again
• Mark Zuckerberg’s Former Top AI Scientist Reveals Exactly Why He Quit