Small language models will be where most algorithmic breakthroughs come from (crowdsourced)

Small language models will be where most algorithmic breakthroughs come from (crowdsourced) | At the high end, scaling hypothesis seems to continue to hold. There are no glass ceilings... But at the small end, I'm pretty sure that we'll look back in a few years time and we'll see at the small end... that's where the algorithmic innovations are going to come from and those can be crowdsourced.

At the high end, scaling hypothesis seems to continue to hold. There are no glass ceilings... But at the small end, I'm pretty sure that we'll look back in a few years time and we'll see at the small end... that's where the algorithmic innovations are going to come from and those can be crowdsourced.

Beneficiaries (24)

Adverse (6)

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  "role": "Host",
  "context": "At the high end, scaling hypothesis seems to continue to hold. There are no glass ceilings. we'll just build bigger and better and more post-trained models. But at the small end, I'm pretty sure that we'll look back in a few years time... that's where the algorithmic innovations are going to come from and those can be crowdsourced.",
  "to_year": 2030,
  "verbatim": "At the high end, scaling hypothesis seems to continue to hold. There are no glass ceilings... But at the small end, I'm pretty sure that we'll look back in a few years time and we'll see at the small end... that's where the algorithmic innovations are going to come from and those can be crowdsourced.",
  "conv_cues": "pretty sure",
  "direction": "HAPPEN",
  "from_year": 2027,
  "timeframe": "Few years",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "prereq",
      "label": "Nvidia became the world's first $5 trillion company (late 2025), operating a near-monopoly on advanced AI chips.",
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      "label": "Nvidia's Arizona-based TSMC factory successfully fabricated cutting-edge semiconductors on US soil for first time in decades (October 2025).",
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      "status": "hit",
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      "expected_date": "2026-04-29",
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      "label": "Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) a",
      "status": "hit",
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      "label": "Open-source SLM <=10B parameters matches GPT-4-class score on MMLU/HellaSwag",
      "source": "Phi-4-mini 3.8B / Mistral / Gemma-2 trajectory 2026",
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      "confidence": 0.85,
      "source_url": "https://localaimaster.com/blog/small-language-models-guide-2026",
      "expected_date": "2026-12-31",
      "research_origin": "deep_research",
      "measurement_criterion": "Public benchmark report (HuggingFace Open LLM Leaderboard, Stanford HELM, lmsys-chat) shows model <=10B params scoring within 5% of GPT-4 (Mar-2024) on standardized MMLU and HellaSwag"
    },
    {
      "kind": "llm_pre_event",
      "label": "Crowdsourced fine-tune of <13B base model tops a major task leaderboard",
      "source": "Wissner-Gross crowdsourcing thesis",
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... (truncated)