Good morning Here's what's happening in AI today: 1. OpenAI Launches ChatGPT Health Connecting Medical Records to AI What happened: OpenAI announced ChatGPT Health, allowing users to securely connect medical records and wellness apps directly to the chatbot. Not intended for diagnosis or treatment, it's designed to help navigate everyday health questions using your own health data. Why it matters: This is OpenAI's major push into healthcare after months of preparation. Sam Altman previously told CNBC that healthcare showed the "strongest improvement of any category" with GPT 5. Hundreds of millions of people already ask health questions weekly. The setup: ChatGPT Health has its own dedicated space, keeping all health files and conversations separate from other chats. Developed in close collaboration with physicians according to OpenAI. Our take: This is both useful and risky. Grounding responses in your actual medical records could make advice more relevant. But we've seen lawsuits from people claiming chatbot advice caused harm. OpenAI is walking a tightrope here. Source: https://www.cnbc.com/2026/01/07/openai-chatgpt-health-medical-records.html 2. 2026 Is the Show Me the Money Year for AI Companies What happened: Industry experts say 2026 is when AI companies must prove real ROI. Boards will "stop counting tokens and pilots and start counting dollars" according to EY's global tech sector leader. Why it matters: The free spending era is over. 68 percent of CEOs plan to spend even more on AI in 2026, but investors and boards are demanding actual returns. No more pitches, no more promises, just profits. The pressure: Companies could go bankrupt from aggressive AI spending if ROI doesn't materialize. On the flip side, we'll see major AI IPOs and GDP growth could jump 100 basis points in America if AI delivers. Our take: This separates real businesses from vaporware. Companies that can't demonstrate clear value by year end are toast. The reckoning is here.

Good morning! Here's what happened in AI over the last 24 hours: 1. Goldman Sachs Warns: US Power Grids Will Hit Breaking Point by 2030 What happened: Goldman Sachs analysts warned that almost ALL US power grids will run out of spare capacity by 2030 as AI data centers drain electricity at unprecedented rates. Most grids aim for 15% reserve margins. They're already falling short. Why it matters: This isn't theoretical anymore. The AI boom could literally run out of power. Goldman says this bottleneck could hand China the lead in the AI race if the US can't build infrastructure fast enough. The numbers: Data center power demand will surge 165% by 2030. US utilities need $50 billion just for new generation capacity. Global grid upgrades could cost $720 billion. Our take: This is the unsexy infrastructure crisis nobody's talking about. Everyone's focused on who has the best model, but if there's no power to run the data centers, it doesn't matter. Expect energy costs to become a major AI story in 2026. Source: https://finance.yahoo.com/news/goldman-sachs-warns-us-grids-164159112.html 2. AMD's Lisa Su: AI Is Reshaping Jobs, Not Replacing Them What happened: At CES, AMD CEO Lisa Su pushed back on the "AI will take all our jobs" narrative, saying AI is changing hiring patterns rather than eliminating roles entirely. Why it matters: This is the messaging battle of 2026. Tech CEOs need people to embrace AI, but workers are scared. Su's framing it as transformation, not replacement. Our take: She's half right. AI IS creating new job categories (prompt engineers, AI trainers, model evaluators). But let's be real, some jobs ARE disappearing. The question is whether new ones appear fast enough. Jury's still out. Source: https://english.cw.com.tw/article/article.action?id=4547 3. Nvidia and Siemens Team Up on "Industrial AI Operating System"

Good morning Here's what's happening in AI today: 1. Chinese AI Firm MiniMax Rockets 78 Percent on Hong Kong Debut What happened: MiniMax Group, a Chinese AI startup, surged 78 percent on its first day of Hong Kong trading, reaching an $11.6 billion valuation. Founded in 2022, they make popular consumer apps like Hailuo AI (video generation) and Talkie (AI character chat). Why it matters: This is the second Chinese "AI tiger" to go public this week, following Zhipu AI which climbed 13 percent on debut. Investors are hungry for Chinese AI exposure, especially consumer focused apps rather than enterprise tools. The contrast: MiniMax's consumer apps drove excitement while Zhipu's enterprise and government focus was "more stable but less exciting." This tells you what investors actually want: consumer viral hits, not boring B2B deals. Our take: China's AI IPO pipeline is hot. DeepSeek (the model everyone's talking about) hasn't announced IPO plans yet, but Huawei's AI server spinoff, Baidu's chip arm, and others are all lining up. Expect more Chinese AI listings to flood markets in 2026. Source: https://finance.yahoo.com/news/china-ai-firm-minimax-set-012942121.html 2. AI Compute Shifts from Training to Inference at CES 2026 What happened: At CES, the big money is moving from training large models to running inference (actually using the models). This marks a fundamental shift in where AI spending flows. Why it matters: For years, companies threw billions at training bigger and bigger models. Now they're realizing inference (making models actually do work) is where the bottleneck is. This changes which companies win. Who benefits: Inference requires different hardware than training. Companies optimizing for inference efficiency (not just raw training power) become more valuable. This is why everyone's talking about edge AI and smaller models. Our take: The training arms race is slowing. The new race is who can run AI cheapest and fastest for actual users. Expect 2026 to be the year of inference optimization over training scale.

Good morning, Crew! Here's what's happening in AI today: 1. AI Industry Quietly Kills AGI Talk What happened: Major AI CEOs are backing away from AGI (Artificial General Intelligence) as a goal. Sam Altman called it "not a super useful term." Anthropic's CEO says he's "always disliked" it. Salesforce CEO called AGI hype "marketing hypnosis." Why it matters: For years, AGI was THE endgame. Companies raised trillions promising to build it. Now they're quietly admitting current tech probably can't get there. This is a massive narrative shift. The receipts: OpenAI defined AGI as systems generating $100 billion in profits. Microsoft CEO says AGI "is never going to be achieved anytime soon." Even the companies building these systems don't believe their own hype anymore. Our take: This is healthy. The AGI narrative was always more marketing than reality. LLMs are powerful tools, not superintelligent gods. The industry is finally admitting what skeptics said all along: you can't just scale your way to human level intelligence. Source: https://gizmodo.com/will-2026-be-the-year-that-the-ai-industry-stops-crowing-about-agi-2000707012 2. AI Moves From Hype to Pragmatism in 2026 What happened: Industry analysts say 2026 will be the year AI shifts from "building ever larger models" to "making AI actually usable." Focus is moving to smaller models, practical deployments, and systems that integrate into real workflows. Why it matters: The brute force scaling approach is hitting limits. Power costs, diminishing returns, and lack of clear ROI are forcing a reality check. 2026 is about proving AI can actually do useful work, not just impressive demos. The trend: World models are rising (AI that understands 3D space and physics, not just text). Agentic workflows are standardizing through protocols like Anthropic's MCP. The party isn't over, but the industry is sobering up.

Good evening! Welcome to your first Daily Pulse. Here's what's happening in AI right now: 1. Nvidia Unveils "Vera Rubin" - Their Next-Gen AI Superchip What happened: At CES 2026 in Las Vegas, Nvidia announced the Vera Rubin platform - combining one Vera CPU with two Rubin GPUs into a single superchip designed for agentic AI and advanced reasoning models. Why it matters: This is the hardware that powers the AI revolution. These chips are what Microsoft, Google, Amazon, and Meta are spending billions to buy. The NVL72 server combines 72 GPUs into one massive system. Our take: Nvidia's market cap is $4.6 trillion for a reason. They're maintaining their dominance even as competitors try to catch up. If you're wondering why AI is advancing so fast, this is why - the compute power keeps doubling. Source: https://finance.yahoo.com/news/nvidia-launches-vera-rubin-its-next-major-ai-platform-at-ces-2026-230045205.html 2. Intel Launches Core Ultra Series 3 - First Chips Built on US-Made 18A Process What happened: Intel unveiled their Core Ultra Series 3 processors at CES - the first AI PC chips built entirely in the United States using their advanced 18A manufacturing process. Pre-orders start today. Why it matters: Intel claims up to 1.9x better performance on LLM tasks. More importantly, this is about AI moving from the cloud to your laptop - processing AI locally means faster responses and better privacy. Our take: The AI PC race is heating up. Expect every new laptop in 2026 to have "AI capabilities" as a selling point. Whether consumers actually care remains to be seen. Source: https://newsroom.intel.com/client-computing/ces-2026-intel-core-ultra-series-3-debut-first-built-on-intel-18a 3. 40 Million People Use ChatGPT for Healthcare Questions Daily