Indeed.
Each technological wave tends to redefine the underlying systems that support progress, and AI seems to be following that same pattern.
MARKET TRENDS
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AI Redefines Underlying Systems Supporting Technological Progress
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DataScience Trends: AI, GenerativeAI, and BigData Insights
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#DataScience Trends by @Python_Dv #AI #GenerativeAI #BigData
→ View original post on X — @ronald_vanloon, 2026-04-07 11:20 UTC
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Google’s GPU dominance benefits Anthropic partnership deal
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Google has the equivalent of roughly 5 million Nvidia H100 GPUs! Therefore, it's no surprise that Anthropic's needs are now benefiting Google. As I said yesterday, Google is exceptionally well-positioned: strong revenue streams, its own chips, and above all: distribution. Anthropic is now also selling shovels for the gold rush. Anthropic (@AnthropicAI) We've signed an agreement with Google and Broadcom for multiple gigawatts of next-generation TPU capacity, coming online starting in 2027, to train and serve frontier Claude models. — https://nitter.net/AnthropicAI/status/2041275561704931636#m
→ View original post on X — @kimmonismus, 2026-04-07 10:34 UTC
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Top AI Stories: OpenAI Society Plans, Meta Models, New Tools
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Top stories in AI today: – OpenAI’s ‘social contract’ ideas for society, ASI
– New Yorker surfaces secret memos behind Altman's firing
– Stress test business ideas with Perplexity
– Wang's first Meta models getting ready to ship
– 4 new AI tools, community workflows, and more -
5G Connectivity Enables Immersive 3D Fitting Experiences Outdoors
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Connectivity becomes an operational enabler in use cases like this. Extending 3D fitting into real environments requires consistent data capture and transfer, because outside controlled spaces, the network directly shapes the quality of the experience. @TMobileBusiness
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Humanoid Robots: From Demos to Real-World Integration
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Humanoid robots are improving fast. What’s changing isn’t just capability, it’s proximity. AI is moving from screens into physical spaces, where it can act, assist, and interact in real environments. That raises a different set of questions. Not about performance in demos. But about reliability in everyday situations. Safety. Trust. Integration into daily routines. The technology is advancing quickly. Adoption will depend on how well it fits into real life. #Robotics #AI #Humanoids #Innovation #FutureOfWork Source 👍🏻Alvin Foo
→ View original post on X — @mvollmer1, 2026-04-07 10:02 UTC
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AI Competitiveness: Internal Use, Industrialization, Model Control
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My takeaway is simple: The next 2 to 3 years will reward companies that do 3 things well: → use AI internally, so leadership understands it firsthand → build with a clear path from pilot to industrialization → take control of their own models, data, and evaluation strategy That is how AI stops being a demo and starts becoming a competitive moat. And now the tools are here: Mistral AI Forge makes model customization accessible, powered by NVIDIA infrastructure, while the NEMO Tron coalition is building an open ecosystem to democratize AI development. Watch more NVIDIA GTC replays at nvda.ws/45K2sCw
→ View original post on X — @ronald_vanloon, 2026-04-07 10:00 UTC
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Open Models as Strategic Advantage for Enterprise AI Differentiation
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The second big insight, open and custom models are becoming a strategic advantage, not just a technical preference. Why? → More control over your AI stack → Less vendor lock-in → Better fit for regulated industries → More value from your own enterprise data and IP General models are strong generalists. But real differentiation comes when you make AI an expert in your domain, your workflows, your business. That’s exactly where the market is heading: With Mistral AI Forge, enterprises can build and fine-tune their own models, while NVIDIA’s NEMO Tron coalition is accelerating open innovation across models, datasets, and tooling.
→ View original post on X — @ronald_vanloon, 2026-04-07 10:00 UTC
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Enterprises Need Better AI Model Evaluation, Not More Pilots
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Most enterprises do not have an AI model problem.
— Ronald van Loon (@Ronald_vanLoon) 7 avril 2026
They have an evaluation problem.
That was one of my biggest takeaways from my conversation with @karibriski from Nvidia and @Toucas from Mistral AI at GTC.
In the agentic era, the winners will not be the companies running the… pic.twitter.com/nY2Jj94KSvMost enterprises do not have an AI model problem. They have an evaluation problem. That was one of my biggest takeaways from my conversation with @karibriski from Nvidia and @Toucas from Mistral AI at GTC. In the agentic era, the winners will not be the companies running the most pilots. They will be the ones that can measure what actually works, scale it, and turn it into revenue. And the ecosystem is evolving fast: → Mistral AI announced Forge, enabling enterprises to build and customize their own models using their data and IP → Powered by NVIDIA’s accelerated infrastructure → NVIDIA also introduced the NEMO Tron coalition to build open models, datasets, and tools Here’s the breakdown. #NVIDIAPartner #NVIDIAGTC
→ View original post on X — @ronald_vanloon, 2026-04-07 10:00 UTC
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Positioning AI Team Strategy Beyond Chatbots and Terminals
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Not a chatbot. Not a terminal. An actual team. The positioning alone on this is genius.