AI Coding Live News

Axion 1.0 Open Agent Foundation Model: Two SFT Stages Plus RL, 35B-A3B Reproduction Checkpoint Under Apache 2.0, Full Recipe Released

arXiv paper 2611.03233 by Yuqi Jia, Yunjie Tian and five co-authors introduces Axion 1.0, an agent foundation model that is open beyond its weights. It uses just two lightweight SFT stages plus reinforcement learning, with no dedicated mid-training, DPO or on-policy distillation, and about 18K SFT trajectories in total. Training code is hosted under the bytedance GitHub organization, and the training data and an Axion 1.0-35B reproduction checkpoint (Qwen3.6-35B-A3B base, 35B total / 3B active, Apache 2.0) are on Hugging Face; weights for the paper's 122B model are listed as coming soon.

Axion 1.0 Open Agent Foundation Model: Two SFT Stages Plus RL, 35B-A3B Reproduction Checkpoint Under Apache 2.0, Full Recipe Released

Key Takeaways

  • A minimal recipe: SFT stage one for self-contained scientific reasoning, stage two for tool use and information seeking, then RL for long-horizon interaction, with 18,363 SFT trajectories and 484 RL tasks
  • The release covers data construction, generation, filtering, verification, prompts and training code (GitHub), not just weights
  • The 35B reproduction checkpoint scores 52.8 on HLE, 60.4 on SEAL-0, 85.0 on FrontierScience Olympiad and 55.0 on FrontierScience Research (HF model card)
  • The paper's 122B model reports 59.0 on HLE with restricted website access and 66.7 on FrontierScience Research; 122B weights are not out yet
  • All scores are self-reported; the HF card lists Claude Opus 5 at 63.6 on HLE, so Axion still trails the strongest closed models
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Linked Models & Agents:
⚡ Axion 1.0-35B⚡ Axion 1.0-122B⚡ Qwen3.6-35B-A3B🌐 ByteDance🌐 Hugging Face

X Discussion: Sam Altman Says People Should Always Control the Future and That This Should Ultimately Constrain AI Progress

At 01:40 UTC on November 4, OpenAI CEO Sam Altman (@sama) posted on X that "people should always be in control of the future," saying OpenAI is against the idea of people being relegated to doing things that "AI systems think makes sense to reward in humans," and that people should not cede control of the future to superintelligence, a requirement that "should ultimately constrain AI progress." Within about 25 minutes it drew roughly 1,360 likes, 337 replies and nearly 100K views; Francois Chollet and others voiced support while many replies pushed back. This is Altman's stated view, not a new OpenAI policy or product announcement.

Key Takeaways

  • Engagement: about 1,360 likes, 337 replies, 89 reposts, 74 quotes and roughly 99K views within about 25 minutes (per the X API); the high reply ratio signals a contested post
  • Three core lines: people should always be in control of the future; OpenAI rejects people being relegated to doing what "AI systems think makes sense to reward in humans"; people should not cede the future to superintelligence, and that requirement "should ultimately constrain AI progress"
  • Support: Francois Chollet (@fchollet) posted "Co-sign," saying the only future worth building is one where AI remains a tool in human hands; Matthew Berman said Altman made the same point in their interview last week
  • Pushback: replies asked "which people?", argued that AI systems "don't think anything," or contrasted the post with Altman's recent comments on RAM and concentrating compute in data centers
  • The post does not say where the quoted phrase comes from and names no concrete policy or timeline; online links to a GPT-6.2 Astra release date are speculation
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Anthropic's Amended S-1 Says Future Models May Imminently Meet Its RSP Threshold for Dramatically Accelerated AI Progress

On November 2 Anthropic filed Amendment No. 1 to its S-1 with the SEC, adding a risk disclosure: based on internal estimates and expectations about future models, not current ones, the company may imminently meet its Responsible Scaling Policy definition of dramatically accelerated progress attributable to AI. No current model has been designated as exceeding the threshold. Anthropic says it is evaluating the implications of meeting the AI R&D capability threshold, is considering RSP updates that would require human review and approval of certain R&D decisions, and does not expect to safely let Claude fully autonomously design and build successive frontier models without meaningful human supervision.

Key Takeaways

  • Filing: Anthropic, PBC's Amendment No. 1 to Form S-1, filed November 2, 2026 (SEC filing), Registration No. 333-299633.
  • Key line: based on internal estimates for future models, the company may imminently meet the RSP definition of dramatically accelerated progress attributable to AI; no current model has been designated as exceeding it.
  • Proposed measures: possible RSP updates requiring human review and approval of certain R&D decisions; Anthropic also says it recently delayed pre-training a new frontier base model by more than a month to strengthen safeguards such as preventing weight exfiltration.
  • Same filing (company figures): over 90% of contributions to Anthropic's codebase in September 2026 were written by Claude, and revenue for the three months ended September 30, 2026 was $17.0 billion.
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X Discussion: Wharton Finance Professor Sylvain Catherine Says His $200/Month Claude Plan Is Worth It, Yet Calls for AI Regulation and No Race to Superintelligence

Wharton associate finance professor Sylvain Catherine posted on X that his views on AI have "radically shifted": he loves the tools and pays $200/month for Claude, but thinks the industry should be far more regulated and that frontier labs need not race toward superintelligence. The post drew about 48K views and 389 likes and is being shared in AI policy circles.

Key Takeaways

  • He pays $200 a month for Claude and calls it "worth every penny, probably even more", and believes current tools can significantly raise future GDP.
  • He cannot see why the industry is not more regulated when its own leaders and employees ask for it, and urges readers to spend an hour on the full chain of events of the Hugging Face incident.
  • He argues large gains are available by deploying current technology in economic and scientific organizations, without pursuing superintelligence.
  • His median scenario matches many economists: slow diffusion, roughly one extra percentage point of GDP growth, disruption along the way, and new jobs in the end.
  • This is an opinion discussion, not a factual report; he says he is not trying to convince anyone, only urging people to get informed and vote accordingly.
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X discussion: Scott Alexander's "Against SURA" criticizes the "stop unilaterally and raise awareness" line, as AI safety is accused of acting like a mass political movement

On October 31, Scott Alexander published "Against SURA" on LessWrong. He uses SURA (Stop Unilaterally + Raise Awareness) for the view that AI companies, their employees and countries should halt AI work on their own and focus on raising awareness, and argues it would hand the lead to companies that do not prioritize alignment and cost the US its bargaining chip with China. He cites AI Futures Project members' survival estimates for scenarios without a global pause, mostly in the 25%-50% range, to push back on 90%+ doom estimates. Blogger jessicat quoted it and said parts of AI safety now behave like a mass political movement with bad epistemics (about 359 likes, 63K views); Bloomberg Odd Lots co-host Joe Weisenthal summed it up as people competing to out-doom each other (about 287 likes, 38K views). This is an opinion debate, not a policy announcement from any organization.

X discussion: Scott Alexander's "Against SURA" criticizes the "stop unilaterally and raise awareness" line, as AI safety is accused of acting like a mass political movement

Key Takeaways

  • Source: Scott Alexander's "Against SURA" on LessWrong, posted 2026-10-31 19:32 UTC; SURA stands for Stop Unilaterally + Raise Awareness
  • AI Futures Project members' survival estimates for three no-global-pause scenarios (C+ / C / D), as cited: Daniel Kokotajlo 40%/20%/10%, Ryan Greenblatt 60%/63%/55%, Eli Lifland 50%/45%/32%, Thomas Larsen 45%/35%/20%, Romeo Dean 40%/35%/20%; the AI forecaster FutureSearch gave 44%
  • He says that if the US unilaterally passed Sanders' "Ban Artificial Superintelligence Act" (endorsed by MIRI), the AI forecaster he asked put the chance of China agreeing to a pause within a year at only 7%, up from 1%
  • jessicat's quote post (Oct 31, 23:01 UTC) has about 359 likes, 28 reposts and 63K views; Joe Weisenthal's quote (Nov 1, 14:57 UTC) has about 287 likes, 33 replies and 38K views
  • Note: the "10-40%" in Weisenthal's post is his paraphrase; the estimates in the essay's table range from 10% to 63%
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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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X discussion: is GPT-6 Astra robotics' "GPT-3 moment"? Ex-OpenAI researcher Will Depue says specialized ML got "bitter lessoned"

Over the past day, X has been debating whether GPT-6 Astra can work directly as a robot policy. Former OpenAI researcher Will Depue (whose bio lists Sora 1 and 2 and o3/4o post-training) called Astra beating specialized robotics models "deeply surprising", then described it as "the final death of specialized ML". Investor Freda Duan posted that "Astra IS robotics' GPT-3 moment", drawing about 84K views. Third-party evaluations point both ways: in a RoboDojo paper, Astra averages 22.48% success and ranks above all 40 public policies, while an EBench report puts it at 46.7%, third of nine models. This is a discussion of opinions, not an official OpenAI conclusion.

X discussion: is GPT-6 Astra robotics' "GPT-3 moment"? Ex-OpenAI researcher Will Depue says specialized ML got "bitter lessoned"

Key Takeaways

  • Reach: Will Depue's two posts have about 597 and 566 likes and 59K and 37K views; Freda Duan's "10 takes" has about 455 likes, 559 bookmarks and 84K views (as of 19:10 SGT)
  • RoboDojo: over 42 tasks and 2,100 trials, Astra averages 22.48% success (Score 28.97), ranking above all 40 public policies; GPT-5.5 gets 0.88% in the same setup (arXiv 2609.24170, as reported by the paper's authors)
  • Counterpoint: in the EBench report, Astra with single-shot in-context learning scores 46.7%, behind OpenWAM-alpha at 55.3% and AMapbot 1 at 48.9% (EBench tech report)
  • Real arms: Robocurve measured 19 of 20 successes on a block-into-bowl task on YAM arms at about $0.94 per run, but only 2 of 20 on a puzzle insertion task (Robocurve)
  • Weak spots: several evaluations find Astra clearly weaker on high-precision control, dynamic control and bimanual coordination
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Anthropic adds two sentences to Claude Code's Opus 5.5 prompt to steer it away from recreating specific existing games; original and genre games still allowed

Around Oct 27, users noticed Claude Code receiving a new server-side rule (flag name tengu_heron_brook): build original games, games in a genre, and games from the user's own designs and assets, but do not build a recreation of a specific existing game, even if it is renamed or called original. The post that surfaced it drew about 8,700 likes and nearly 2 million views on Oct 30. The same day, Addy Osmani, who works on Claude Code at Anthropic, confirmed on X that the team added two sentences to Claude Code's prompt on Opus 5.5 because using Claude to infringe IP is against Anthropic's usage policy. He said original games, genre games, and games built from your own designs and assets should keep working, that the team will keep iterating, and that users can send him wrongly refused requests.

Key Takeaways

  • Scope: the change is just 2 sentences in Claude Code's system prompt for Opus 5.5, pushed from the server with no user-side toggle (Addy Osmani's post)
  • Rule text (per the flag tengu_heron_brook users captured): original games, genre games, and games from the user's own designs and assets are allowed; a recreation of a specific existing game is not, "even if it is renamed or called original" (original report, about 8,700 likes and nearly 2M views)
  • Basis: Anthropic's Usage Policy prohibits using its products to infringe, misappropriate, or violate a third party's intellectual property rights
  • Feedback path: Osmani says the team will keep tuning the line and asked users to send him wrongly refused requests; there is no separate Anthropic blog post yet, and benchmarks do not apply
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OpenAI, Google, Microsoft and Anthropic back one robots.txt AI-training opt-out token, __usage_ai-training; Anthropic has started, Microsoft honors it from Feb 1, 2027

On October 30, OpenAI, Google, Microsoft and Anthropic each published posts committing to one shared robots.txt training-preference signal: a site writes a single Disallow group for the policy token __usage_ai-training to tell every participating provider not to use its content for generative AI training. The mechanism comes from an IETF individual Internet-Draft filed that day by Anthropic standards lead Kevin Kelley and is not yet a formal standard. Timelines differ: The Verge and CNA report Anthropic has already started implementing it, OpenAI says "in the coming months", Microsoft honors it from February 1, 2027, and Google plans support during 2027.

Key Takeaways

  • Syntax: in robots.txt, User-Agent: __usage_ai-training plus Disallow: / states a site-wide preference against AI training, and Allow rules can carve out paths such as /press-kit/; omitting the group means no preference is expressed
  • Draft: draft-kelley-aipref-training-preference-signal-00 by Kevin Kelley (Anthropic), filed 2026-10-30 and expiring 2027-05-03, an individual IETF draft with no formal standing yet
  • Timeline: Anthropic has reportedly started; OpenAI says "in the coming months"; Microsoft honors it from 2027-02-01 and sites relying on NoArchive/NoCache should migrate by 2027-03-01; Google plans support in 2027
  • Training only, not crawling: the draft says the token is not a crawl directive, wildcard User-Agent: * groups do not match it, and existing GPTBot, ClaudeBot and Google-Extended rules keep working
  • Microsoft also adds a page-level AI Grounding preference whose new DisallowExtended value limits grounding to Microsoft's own products (Copilot, AI Overview and others) and excludes third-party grounding services such as Foundry API access
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Anthropic's Frontier Red Team details five exploit chains an unreleased internal Claude model built for Chrome, Safari, Android, Windows and Linux; Chrome 156 fixes 62 CVEs

Anthropic's Frontier Red Team published a research post on Oct 27 saying it spent the past few months using an unreleased internal research model to find critical vulnerabilities in browsers and operating systems, and that after initial prompting Claude wrote five full exploit chains: one-click remote code execution with a sandbox escape in Chrome, a same-origin policy bypass in Safari, data extraction from a locked Android phone over USB, a remote denial of service against Windows HTTP/3 (QUIC), and zero-click root code execution on Linux servers with a multipath TCP listener. Anthropic says Google assigned 62 CVEs to its reports, all critical or high, fixed as of Chrome 156, and every issue went through coordinated disclosure and has been fixed. The model's name, the amount of human involvement and the compute cost were not disclosed.

Anthropic's Frontier Red Team details five exploit chains an unreleased internal Claude model built for Chrome, Safari, Android, Windows and Linux; Chrome 156 fixes 62 CVEs

Key Takeaways

  • The Chrome chain links 4 bugs: V8 heap corruption, a V8 sandbox escape that defeats ASLR, a CacheStorage race condition and a FedCM use-after-free; the PoC launches Calculator within seconds of a page loading in default Chrome on macOS
  • Per Anthropic, Google assigned 62 CVEs to its reports, all critical or high, including 13 sandbox escapes and 21 renderer-compromise bugs, fixed as of Chrome 156
  • The Windows kernel QUIC out-of-bounds read is CVE-2026-33096, with likely several million exposed servers by Anthropic's estimate; the Linux MPTCP zero-click root bug is CVE-2026-98432, where the PoC leaks a kernel pointer in about 48 minutes and reaches root command execution about 5 minutes later
  • Method: many parallel scanning agents scored by the extra vulnerabilities they add, with coverage tracking and automated variant analysis on every confirmed finding; Anthropic recommends scanning at PR time and has released a Claude Code security plugin
  • The model is an unnamed internal research model; Anthropic did not publish the share of human work, failed attempts or compute cost
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Linked Models & Agents:
⚡ Claude (unreleased internal research model)🤖 Claude Code🌐 Anthropic🌐 Google🌐 Apple🌐 Microsoft
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X discussion: Anthropic engineering manager Felix Rieseberg says he dropped coding interviews for his team, arguing "hunger beats tenure", and the post passes 1M views

Felix Rieseberg, whose X bio says he builds things at Anthropic, posted on Oct 27 that the coding interview is "dead, at least for my team at Anthropic" and that he removed it from his hiring loops this month, linking an essay titled "Hunger beats tenure" with advice for junior engineers. The post drew about 9,500 likes, over 1 million views and more than 10,000 bookmarks, sparking wide debate. This is his personal view and his teams practice, not an official Anthropic hiring policy.

Key Takeaways

  • Felix Rieseberg's post: coding interviews no longer provide signal, and he removed them from his own team's loops this month
  • His essay's reasoning: Claude now beats people at small React challenges, and the team's most impactful builders succeed regardless of how they score on such tests
  • His optimistic take: AI makes execution cheap, so engineers without tenure can skip PRDs and approval layers by building a working prototype over a weekend
  • His example: the graphical version of Claude Code began as a weekend prototype by two relatively new engineers, Anthony Morris and Alice Zhao, and first shipped publicly about eight days later
  • The post has about 9,500 likes and over 1M views; it is one manager's view and practice, not Anthropic's company-wide hiring policy
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Anthropic releases a Claude for Nonprofits plugin with fundraising, marketing and hiring skills built with ~30 organizations

On Oct 26 Anthropic released the Claude for Nonprofits plugin, a set of skills and connectors built with about 30 nonprofits. It covers the full fundraising cycle (finding funders, breaking down RFPs, drafting proposals and reports, donor stewardship), marketing, hiring and board work, and starts by having Claude map where the organization keeps its records and answer questions against the organization's own AI policy. It is installed automatically at no extra cost for verified nonprofits on Team and Enterprise plans. Anthropic says more than 25,000 nonprofits use Claude, and over 75% of them have fewer than 10 seats.

Anthropic releases a Claude for Nonprofits plugin with fundraising, marketing and hiring skills built with ~30 organizations

Key Takeaways

  • Scale (vendor-reported): more than 25,000 nonprofits use Claude, and over 75% of them have fewer than 10 seats, per the official article
  • How it was built: about 30 design-partner organizations, including the IRC, the Gates Foundation and International Justice Mission, tested early skills on real work and fed back changes
  • Pricing: the plugin is installed automatically at no extra cost on nonprofit Team and Enterprise plans; nonprofit discounts reach 75%, and about 90% in low- and middle-income countries, bringing Team seats to $3/user/month, with Claude Code included
  • Talent: Claude Corps is placing 1,000 early-career fellows in at least 400 US nonprofits, and Anthropic plans to extend it with Taproot for shorter pro bono projects
  • Onboarding: two official webinars run on Nov 10 (admins, data handling and AI policy) and Nov 12 (staff, day-one use)
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X discussion: viral posts claim Anthropic "quietly killed" Claude's reverse engineering with the REA toolkit after a Samsung TV firmware teardown went viral; no official statement yet

One of the hottest AI developer topics on X over the past day. At 21:55 UTC on 2026-10-23, security account @0x0SojalSec (Md Ismail Šojal) posted that "Claude can no longer Reverse Engineer Anything" and that "Anthropic just quietly killed REA", tying the timing to viral cases of people using Claude to reverse engineer Samsung TV firmware and find data-collection services; the post had about 8,345 likes, 1,055 reposts and 514K views. An earlier post making the same claim by @AbhinavXJ had about 10,477 likes and 640K views. As of this run we found no statement from Anthropic or its staff, and some users replied that it still works for them. These are user reports and opinions on X, not a confirmed policy change.

X discussion: viral posts claim Anthropic "quietly killed" Claude's reverse engineering with the REA toolkit after a Samsung TV firmware teardown went viral; no official statement yet

Key Takeaways

  • Main post: @0x0SojalSec's post, about 8,345 likes, 1,055 reposts, 2,545 bookmarks and 514K views when we pulled it
  • An earlier post making the same claim: @AbhinavXJ's post (11:16 UTC on 10-23) said "anthropic just killed the REA" and argued this is why local models matter; about 10,477 likes and 640K views
  • One trigger was a Samsung TV firmware teardown: @log4j posted that the TV classifies the audio it hears before reporting back, about 6,720 likes; in another post he said his OpenAI account was banned after local reverse engineering work tripped its checks, about 6,454 likes and 729K views
  • REA is an open-source reverse engineering toolkit (GitHub morluto/rea), showing about 377K stars in the GitHub API this run; we covered its viral launch on 10-08
  • We found no response from Anthropic's official accounts or staff this run; some users replied that REA still works for them and is refused only in specific cases, so the real scope awaits an official word
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X discussion: a new paper from Harvard's Gary King says AI article reviews beat top human peer reviews "by every measure we could construct", and Ethan Mollick urges academia to adapt fast

At 00:27 UTC on 2026-10-23, Harvard social scientist Gary King (@kinggary) posted a new paper with Steven Worthington, "AI Article Reviews Dominate Human Peer Reviews at Their Best: Evidence and Policy Choices". Its abstract says AI-generated reviews are now better, by every measure the authors could construct, than reviews by well-compensated human experts that editors and authors judged to be unusually good. Wharton professor Ethan Mollick (@emollick) then wrote that the study covers 124 Harvard social science papers and used Claude Opus 4.8, and that academics need to figure out how to adapt science to AI fast; his post had about 1,675 likes and 97K views. The topic was still on X's trending news list over the past 12 hours. This is an X discussion of a single paper, not a conclusion from any journal or from Anthropic.

Key Takeaways

  • The paper is by Harvard's Gary King and Steven Worthington; its page says it was last updated on 2026-10-22 (paper page; King's post, about 472 likes, 121K views and 371 bookmarks when we pulled it)
  • In the abstract's words, AI reviews are better "by every measure we could construct" than reviews by "well-compensated" human experts judged to be of "unusually high quality"; the paper also discusses journal policy choices and their "concerning downsides"
  • Ethan Mollick's post (post) says the study used Claude Opus 4.8 on 124 papers; it had about 1,675 likes, 97K views and 249 replies when we pulled it
  • Many reposts on X also cite figures such as "former journal editors picked the AI review 87% of the time" and "5.5% vs 15.9% wrong claims"; we have not checked each of these against the paper itself, so treat the paper as the source of record
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NVIDIA launches OpenShell Reference Architecture at GTC Berlin: Vera Rubin, Vera CPUs and BlueField-4 Sentry for hardware-enforced safe AI agents

At GTC Berlin on Oct 21, NVIDIA announced the OpenShell Reference Architecture: building on the open-source OpenShell secure runtime, it pairs Vera Rubin for inference, Vera CPUs for agent harnesses, and BlueField-4 DPUs running NVIDIA Sentry for in-silicon policy enforcement, so enterprises can build, contain, observe and govern agents on-prem and at the edge. NVIDIA says it is available now; partners named include Anthropic, OpenAI, Meta, Microsoft and ServiceNow. The software is Apache 2.0.

NVIDIA launches OpenShell Reference Architecture at GTC Berlin: Vera Rubin, Vera CPUs and BlueField-4 Sentry for hardware-enforced safe AI agents

Key Takeaways

  • Full stack: Vera Rubin for model inference, Vera CPUs for agent harnesses/tool use, BlueField-4 + Sentry for in-silicon policy and quarantine (vendor claims)
  • Vendor claims: Vera Rubin NVL72 about 30x throughput per megawatt on agentic workloads; Sentry can quarantine a boundary-breaking agent in milliseconds and boost agent capacity by up to 20%
  • Runtime: deny-by-default, enforcement outside the agent process; sandboxes have no direct network, syscalls are filtered in-kernel, credentials are injected only onto allowed requests
  • Stated agent paths include Claude Code, Codex, GitHub Copilot CLI, OpenCode, OpenClaw, LangChain Deep Agents; deploy with Docker, Podman or Kubernetes via Helm
  • Start: curl install script then openshell sandbox create; docs at docs.nvidia.com/openshell; GitHub NVIDIA/OpenShell (Apache 2.0) and PyPI package openshell
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