Bloomberg Technology
What if Big Tech’s Massive Bet on AI Is a False Start?
Big tech is spending hundreds of billions on AI. Is it money well spent? Merryn Somerset Webb explains why it could be a colossal false start. ——– Like this video? Subscribe to Bloomberg Technology on YouTube: Watch the latest full episodes of “Bloomberg Technology” with Caroline Hyde and Ed Ludlow here: Get the…
Bloomberg Technology
Crusoe CEO: Data Center Indusry Has a ‘Marketing Issue’
Crusoe CEO Chase Lochmiller discusses the AI infrastructure company’s nearly $4 billion in fresh funding sending its valuation to almost $31 billion. He also discusses how it will fuel the company’s push to build AI infrastructure spanning data centers, cloud computing and managed AI services. He says Crusoe could eventually enter the public markets and…
Bloomberg Technology
Former FTC Technologist Warns Against an AI ‘Cartel’
As frontier AI labs seek greater coordination on safety, Neil Chilson, Head of AI Policy at the Abundance Institute and former FTC Chief Technologist, warns that government-backed antitrust exemptions could create a durable “cartel” that ultimately harms competition. He argues companies can collaborate on safety standards without suspending antitrust rules, and that existing consumer-protection and…
Bloomberg Technology
Anthropic Investor Franklin: AI Safety Concerns Won’t Slow Spending
Calls to “pace” development at the AI frontier are unlikely to translate into a slowdown in infrastructure spending, according to Sara Araghi, Franklin Templeton Portfolio Manager and Franklin Venture Partner. She argues that even if labs temper some model training, growing inference demand will continue to require enormous amounts of compute. Araghi also discusses why…
Play is what happens when you stop trying to optimize everything #TEDTalks
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@truevegas
May 21, 2026 at 4:00 pm
Yes 😂 LLMs can learn on the job though. At least Claude can. You just need to save relevant information in its Artifacts and Projects
@orvn
May 21, 2026 at 4:47 pm
Not training on the job, just adding to context, or in best case, accessing a vector storage db in a serial process. The model doesn’t inherently change until training or fine-tuning. There are no inference-training hybrid models at this time. Just elaborate loops.
@orvn
May 21, 2026 at 4:50 pm
I go with Yan Lecun’s thinking here: language is too limited of a training set source. We need to simulate human sensory input (in a non-synthetic way)