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X discussion: Microsoft AI CEO Mustafa Suleyman posts "Don't build conscious superintelligence", saying AI development should stop if consciousness emerges in training

Microsoft AI CEO Mustafa Suleyman published an X article on November 1 titled "Don't build conscious superintelligence", responding to reactions to his September essay on model welfare. He clarified that his line "AIs are not conscious" was deliberately in the present tense: they are not today, and that is how they must remain. If consciousness started to emerge in training, he would call for everyone to stop AI development until those properties could be designed out. He argued that AI developers have no right to bring a new conscious species into the world and that welfare concerns should focus on humans, animals and the natural environment. He also credited Anthropic for publishing its constitution and research, while saying he disagrees with its approach. The post drew about 353 likes, 251 bookmarks and 290K views, with ethicists and practitioners on both sides. This is a personal opinion piece, not a Microsoft product or policy announcement.

X discussion: Microsoft AI CEO Mustafa Suleyman posts "Don't build conscious superintelligence", saying AI development should stop if consciousness emerges in training

Key Takeaways

  • Original post: @mustafasuleyman X article, Nov 1, 15:22 UTC, about 353 likes, 56 reposts, 79 replies, 251 bookmarks and 290K views at fetch time
  • It responds to reactions to his Sept 16 essay "It's time to talk about model welfare" (about 1,013 likes); his X bio lists CEO of Microsoft AI, author of The Coming Wave, and co-founder of DeepMind and Inflection
  • Core claim: "AIs are not conscious" describes today and that is how it must remain; any evidence of AI consciousness should be disclosed publicly at once; if consciousness emerges in training, development should stop
  • He credits Anthropic for publishing its constitution and a stream of papers and posts, says he disagrees with its approach, and calls for labs to research this together and share safety information
  • In quote posts, UMass Amherst economics and ethics scholar Itai Sher called it "very well put"; UCL professor Tim Colbourn agreed but doubted safety can be engineered by default; others noted there is no accepted theory or test of consciousness
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Linked Models & Agents:

Microsoft makes MAI-Image-2.6 and MAI-Image-2.6-Flash generally available in Foundry as MAI-Image-2.7-Preview reaches #3 in Image Edit Arena

Microsoft AI announced on Oct 27 that MAI-Image-2.6 and MAI-Image-2.6-Flash are generally available in Microsoft Foundry, with multi-reference editing from up to five images, Bing web grounding, output up to 1.5K and published per-token pricing. The same day its next image editing model, MAI-Image-2.7-Preview, reached #3 overall in Arena's Image Edit leaderboard at 1470 points, 45 points above 2.6; for now it is available only for editing in MAI Playground.

Microsoft makes MAI-Image-2.6 and MAI-Image-2.6-Flash generally available in Foundry as MAI-Image-2.7-Preview reaches #3 in Image Edit Arena

Key Takeaways

  • MAI-Image-2.6 and MAI-Image-2.6-Flash are generally available in Microsoft Foundry, and Microsoft says 2.6 is coming soon to Adobe Firefly
  • Official pricing: 2.6 costs $5 text input, $8 image input and $38 image output per 1M tokens; Flash costs $1.75, $2.50 and $19
  • 2.6 supports multi-reference editing with up to five images, Bing web grounding, dynamic aspect ratios and output up to 1.5K
  • Per Arena, MAI-Image-2.7-Preview is #3 overall in Image Edit Arena at 1470 points, 45 points above 2.6 (#7), putting Microsoft AI #2 among labs
  • Per Artificial Analysis, 2.7-Preview is #2 on AA-Image-Editing v2.1 and beats 2.6 on all 7 editing actions, ranking #1 on 4 of them
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Linked Models & Agents:
⚡ MAI-Image-2.6⚡ MAI-Image-2.6-Flash⚡ MAI-Image-2.7-Preview🌐 Microsoft🌐 Microsoft AI

Microsoft AI finishes pre-training MAI-Base-2: 2.8T-total / 80B-active MoE trained on 16K GB200s in 38 days, which MAI estimates is 4.2–12.3x more FLOPs-efficient than DeepSeek-V4-Pro-Base

On 2026-10-15 Microsoft AI published a technical post and PDF saying it has finished pre-training its in-house base model MAI-Base-2: MoE in every layer (1 shared + 7-of-512 routed experts), 80B active / 2.8T total, 102 layers, native encoder-free vision, a 50T-token mixture and a March 2026 knowledge cutoff. Per MAI, it beats every open-weight model tested on held-out BPB and its recipe is 4.2–12.3x more pre-training-FLOPs-efficient than DeepSeek-V4-Pro-Base. It is still in post-training: no API, no weights and no release date yet; Microsoft plans to license weights to trusted partners via Foundry.

Microsoft AI finishes pre-training MAI-Base-2: 2.8T-total / 80B-active MoE trained on 16K GB200s in 38 days, which MAI estimates is 4.2–12.3x more FLOPs-efficient than DeepSeek-V4-Pro-Base

Key Takeaways

  • Scale: 80B active / 2.8T total, 102 layers, hidden 8704, MoE in every layer (1 shared + 7 of 512 routed); MAI-Base-1 was 35B/1T, 78 layers, alternating dense/MoE (PDF)
  • Compute: 16K GB200s for 38 days (Aug–Sep 2026), 21% average MFU (vs 2.5 PFLOPS BF16), 89% goodput; the Muon step is 2.1% (165 ms) of iteration time
  • Efficiency (vendor estimate via scaling-law fits): 4.2–12.3x fewer FLOPs than DeepSeek-V4-Pro-Base to match its BPB; 6.3–12.7x better than the June MAI-Base-1 recipe
  • Data: 50T-token mixture, 18% vision-language (4.5T unique), ~36% more unique tokens than Base-1, described as organic data with no distillation
  • Availability: still in post-training, no API/weights/date; weights to be licensed to trusted partners through Foundry; MAI-Base-3 prep underway (blog)
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Linked Models & Agents:
⚡ MAI-Base-2⚡ MAI-Base-1⚡ MAI-Thinking-1⚡ DeepSeek-V4-Pro-Base⚡ Kimi K3⚡ Qwen3.8-2.4T-A95B🌐 Microsoft🌐 NVIDIA🌐 DeepSeek