This explains why DeepSeek-R1 beats models 10x its size. It's not bigger. It's not trained on more data. It just thinks longer and verifies harder. 32B parameters thinking for 30 seconds > 405B parameters answering instantly. The scaling law just changed from "bigger" to
MARKET TRENDS
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Elastic Intelligence: small model, dynamic per-query scaling
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This makes $100M training runs obsolete. Why spend months training a massive model when you can deploy a smaller one and scale intelligence dynamically per query? Hard math problem? Give it 60 seconds to think.
Simple question? Answer instantly. Intelligence becomes elastic -
Economics flip: small models with more inference match GPT-4
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The economics just flipped completely. Training GPT-4: $100M+ in compute
Inference scaling: $0.10 per complex query You can make a 7B model as smart as GPT-4 by letting it think 100x longer at inference. Smaller models + more thinking time = beats bigger models at fraction of -
OpenAI’s o1 demonstrates smarter models via inference-time compute
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OpenAI's o1 proves you can make models smarter by making them "think longer" at inference not training bigger models. DeepSeek, Google, Anthropic all pivoting to test-time compute. Training wars are over. The inference wars just started. Here's the paradigm shift happening
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Test Your Brand Visibility with ChatGPT
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Honest question: Have you ever tested whether ChatGPT can name your brand without a prompt? If not, you're not measuring AI visibility. You're guessing. [Translated from EN to English]
→ View original post on X — @coremention, 2026-01-15 08:37 UTC
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Meta Lays Off 1,500 Employees in Reality Labs Metaverse Division
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D'après le WSJ, Meta vient de licencier 1 500 employés au sein de sa division Metaverse. Cela fait partie de leurs efforts autour du métaverse via Reality Labs, une division qui a accumulé des pertes cumulées dépassant 70 MILLIARDS de dollars depuis 2020.
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Salesforce joins Hugging Face as major enterprise customer
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Excited to welcome @salesforce as our latest enterprise customer! Already massive contributions (180 public models like Blip) and can't wait for what they'll do next! https://
huggingface.co/Salesforce -
CES Highlights: AI Partnerships, Innovation, and Future Developments
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Last week at CES, we shared what’s next across partnerships, innovation, and the future of AI. If you missed any of it, now’s the perfect time to dive in. pic.twitter.com/sG6SLNa8N2
— NVIDIA (@nvidia) 14 janvier 2026Last week at CES, we shared what’s next across partnerships, innovation, and the future of AI. If you missed any of it, now’s the perfect time to dive in.
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SEO Rankings vs AI Visibility: A Growing Gap for Teams
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We still measure Google rankings in seconds, but most teams have no idea how (or if) they show up in AI answers. The assumption that “good SEO = AI visibility” is becoming risky.
→ View original post on X — @coremention, 2026-01-14 17:42 UTC