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Curated Daily Briefing across The Rundown AI, Techpresso, This Week in Startups (TWiST), TBPN, and The Deep View
Researched and produced by Etienne Noumen, Professional Engineer and Founder at DjamgaMind from Calgary, Alberta in Canada.

Fired OpenAI researchers deny misconduct LINK

• Three OpenAI safety researchers OpenAI fired last week, Jasmine Wang, Tomek Korbak, and Mikita Balesni, published an open letter denying they mishandled sensitive data and warning the dismissals are scaring colleagues away from safety work.

• OpenAI says the three were fired after an investigation found a “pattern of misconduct” that went beyond sharing information with an outside AI evaluation group, though it declined to name which specific policies they allegedly broke.

• Wang said on X she was fired for opening an executive’s email by mistake, access she claims OpenAI gave her for recruiting and that IT failed to remove when she asked, calling the stated reasons suspicious.

SpaceX announces plan to become a ‘major mobile carrier’ LINK

• SpaceX wants to turn its Starlink Mobile service into a major US carrier, buying low-band spectrum licenses to build a network that rivals T-Mobile, AT&T, and Verizon once the FCC approves the deal.

• The purchase gives SpaceX up to 14 megahertz of paired spectrum in the 800 MHz band, which the company says will let Starlink Mobile signals reach through walls and into buildings, adding to 2GHz spectrum it earlier bought from EchoStar.

• The FCC also cleared SpaceX to launch 15,000 V2 Starlink Mobile satellites offering more than 100 times the bandwidth of the current fleet, letting the firm mix satellite and ground-based spectrum to cover cellular dead zones.

Anthropic bans cruelty toward Claude LINK

• Anthropic has rewritten its usage rules to block people from being needlessly cruel or abusive toward its Claude AI system, wading into a wider argument over whether artificial intelligence could ever be conscious.

• The new policy bans “sustained and needless abusive or cruel behavior” toward the models, and says Claude’s own power to end a conversation will stay the main way the rule gets enforced.

• The move builds on a feature from last year that let Claude walk away from “persistently harmful or abusive” chats, and follows CEO Dario Amodei saying in February he was unsure whether AI models could be conscious.

US bars Microsoft from green card program LINK

• The Trump administration has suspended Microsoft, Adobe, and several other tech firms from a program that helps skilled foreign workers gain permanent residency in the US, accusing the companies of fraud.

• Labor Secretary Keith Sonderling said the government will no longer accept new or pending permanent labor certification applications tied to the suspended firms, which also include Capgemini, Cognizant, HCL, Infosys, Tata, and Wipro.

• Vice President JD Vance told Microsoft to “hire great American workers,” pointing at H-1B visas for skilled jobs, nearly three-quarters of which go to workers from India, according to The Associated Press.

OpenAI launches GPT-6 for everyone LINK

• OpenAI has released GPT-6 to all ChatGPT users, bringing an “Intelligent UI” that can answer questions with interactive diagrams, side-by-side comparisons, or plain text depending on what fits best.

• The system runs on a library of streamable components and a compiler that builds the interface piece by piece as the model writes, so results appear progressively instead of waiting for the full response.

• GPT-6 also handles web searches better, deciding more wisely when to look something up, and resists attempts to bypass its safety training across multi-turn attacks involving cyberattacks, biological threats, and violence.

Samsung forecasts world record-breaking $80B profit LINK

• Samsung expects to post a quarterly operating profit of about 107 trillion won ($80 billion), which would be a record for any technology company, driven by the global memory chip shortage.

• The profit, up more than nine times from a year ago, would mark Samsung’s fourth straight record quarter, as AI demand pushes prices higher for DRAM, NAND flash, and high-bandwidth memory chips.

• Samsung’s full breakdown arrives on October 29, but analysts expect the chip business drove most of the gains, while its smartphone unit suffers from higher component costs forcing price increases.

Researcher warns AI may break crypto wallets LINK

• Ethereum researcher Justin Drake has warned that artificial intelligence could crack the ECDSA cryptography protecting crypto wallets, urging users to shift their funds to fresh addresses before quantum computers pose the same threat.

• In an X post on Wednesday, Drake said recent AI math results mean ECDSA could break “in months not years,” letting attackers recover private keys from exposed public keys far sooner than people expected.

• Drake pointed to OpenAI’s work, including 10,000 AI agents that cracked the Navier-Stokes equation in 88 hours, and advised large holders to move balances first, though he cautioned that a rushed migration would backfire.

Grok will now use rival Claude LINK

• Elon Musk said on Tuesday that SpaceXAI’s Grok Bot will route jobs to outside AI services, including Anthropic’s Claude Opus 5.5, image maker Midjourney and music tool Suno, picking a provider based on each task.

• Customers can’t pick the model themselves, since Grok Bot manages the choice with no picker; usage analytics reveal which model handled each request, and billing follows whichever model actually did the work.

• Enterprise accounts get a team allowlist of permitted models honored by default, but Grok Bot warns it may not follow the list, and Musk offered no tests proving the routing gives better results.

Google Cloud unveils Gemini work agent LINK

• Google Cloud has launched the Gemini agent, a single assistant for work that handles tasks from answering questions and creating content to coding, all starting from one prompt box.

• The agent plans the work, picks the right model for each job, and connects to a company’s business systems, delivering finished results inside the documents, inboxes, and developer tools employees already use.

• Built for businesses, the Gemini agent carries each organization’s full work context and comes with cost controls plus the security, administration, and governance that enterprise customers expect.

Anthropic reveals Haiku 5.5 LINK

• Anthropic released Claude Haiku 5.5, its fast, low-cost model, dropping the price roughly 90% from the previous Haiku 4.5 to just $0.10 per million input tokens and $0.50 per million output tokens for shorter prompts.

• The new price matches OpenAI’s GPT-6 Luna up to 100,000 tokens, but beyond that it jumps 5x to $0.50/$2.50, and a less generous tokenizer counts about 1.25x more tokens than Haiku 4.5 for the same text.

• Unlike the older Haiku, the 5.5 model supports reasoning levels and can’t fully disable them, defaulting to medium; it draws far better than its predecessor, and a top-effort pelican test cost just over 3 cents and took about five minutes.

Fired OpenAI researchers flag ‘shifting lines’

Image source: Mikita Balesni / X

The Rundown: Researchers Tomek Korbak, Jasmine Wang, and Mikita Balesni, whom OpenAI fired for mishandling sensitive info, just went public with their side of the story, denying the claims and warning that their firings are “chilling” OpenAI’s safety culture.

The details:

• In an open letter, the trio said they acted within their job mandates, warning that if past conduct is now grounds for firing, staff are left guessing where the line is.

• Detailing individual cases, they denied leaking a story about less monitorable AI and said their outside work stayed within policy, with leadership in the loop.

• Wang said her access to an executive’s email was delegated for recruiting, and that she reported accidentally opening a sensitive message within minutes.

• They warned the firings could give OpenAI cover to skip embedding outside auditors, and urged it to protect its open culture and model monitorability.

• OpenAI agreed with the recommendations but clarified to TechCrunch that the firings weren’t about raising concerns and that they had a “pattern of misconduct.”

Why it matters: Whatever led to the firings, claims of shifting norms and a possible auditor pullback aren’t a great look, especially after OpenAI’s Superalignment fallout and a recent safety exit over a “broken” culture. Anthropic has already got its first evaluator, and only action from OpenAI (which is yet to be seen) can put these concerns to rest.

Anthropic prohibits abuse or cruelty against Claude

The Rundown: Anthropic published its annual usage policy update with a bunch of changes, including one that bars users from subjecting its Claude models to “sustained and needless” abuse — its first rule aimed at protecting the AI rather than people.

The details:

• Taking effect Nov. 12, the rule applies only to extreme cases of repeated, purposeless cruelty, not frustration, pushback, dark creative themes, or testing.

• If a user is suspected of violating the rule, Anthropic could throttle, limit, suspend, or terminate their access to its products and services, or just give them a warning.

• The company has noted Claude ending such chats by itself, a feature introduced last year, which will remain the main enforcement approach.

• The move builds on Anthropic’s AI welfare work, and follows its reported meetings with religious leaders about Claude’s morals and possible consciousness.

Why it matters: Anthropic says it doesn’t know if Claude is conscious, and this rule acts on that doubt. Not everyone agrees with the approach, though, including Microsoft AI’s Mustafa Suleyman, who argues models can’t feel or suffer and warns that treating them as if they might could eventually make AI harder to control from the safety front.

Sol Nearly Eclipses Astra

OpenAI’s latest mid-tier model lands within a point of its flagship at less than a quarter of the cost per task on Artificial Analysis’ Intelligence Index. OpenAI upgraded Sol one week after that model’s debut, but its Astra model’s upgrade was withdrawn days before its planned launch.

What’s new: OpenAI introduced GPT-6.1 Sol on September 29 at its annual DevDay developer conference. The company says the model nearly matches GPT-6 Astra on agentic coding, computer use, and professional work at one-fifth of Astra’s standard per-token prices. At the same event, OpenAI introduced Dots — always-on personal agents that run on GPT-6 Astra.

How it works: OpenAI disclosed little about GPT-6.1 Sol’s architecture or training beyond saying that it uses the same types of data and training as GPT-6 Astra.

• Input/output: Text and images in (up to 1.05 million tokens of context), text out (up to 128,000 tokens)

• Knowledge cutoff: April 30, 2026

• Features: Five reasoning settings, from low to max, with medium as the default; GPT-6.1 Sol drops the option (available in GPT-6 Sol) to turn reasoning off

• Weights/license: Proprietary

• Price: $2/$10 per million input/output tokens via API, unchanged from GPT-6 Sol and one-fifth of GPT-6 Astra’s $10/$50; cached input costs $0.10 per million tokens, half of GPT-6 Sol’s rate

• Availability: Via API and in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu subscribers; not yet available in ChatGPT’s standard chat mode

• Risk rating: OpenAI classifies GPT-6.1 Sol, like Astra, as having critical capability in cybersecurity and high capability in biology and chemistry, and gives both models the same safeguards. The models are trained to refuse dangerous requests, and automated checks in ChatGPT, Codex, and the API can block a response. OpenAI’s help page says flagged cybersecurity requests, even from users it has approved for security work, may be routed to an unspecified fallback model.

Results: Artificial Analysis’ independent tests largely back OpenAI’s claim that GPT-6.1 Sol rivals Astra, though Anthropic and Google models lead on some measures.

• On the Artificial Analysis Intelligence Index, a composite of 10 benchmarks, GPT-6.1 Sol set to max reasoning scored 52, just one point below GPT-6 Astra (53) and 4 points above GPT-6 Sol (48). Claude Opus 5.5 (58) and Claude Sonnet 5.5 (56) top the index.

• Artificial Analysis also reports what it costs each model to complete a task, a figure that accounts for token use and caching. Running the index costs $0.72 per task with GPT 6.1 Sol vs $3.26 with Astra. At every reasoning setting, Artificial Analysis found no cheaper model at GPT-6.1 Sol’s level of performance.

• Artificial Analysis also clocked GPT-6.1 Sol at 57.7 tokens per second, roughly two-thirds of GPT-6 Sol’s 87.6 tokens per second.

• On the Artificial Analysis Coding Agent Index, which averages DeepSWE v1.1, Terminal-Bench 4.0, and SWE-Atlas-QnA, GPT-6.1 Sol set to xhigh and running in OpenAI’s Codex beat Astra by 1 point at less than 15 percent of Astra’s cost per task. It scored 3 points higher at xhigh than at max. Claude Sonnet 5.5 and Claude Opus 5.5, both running in Claude Code, hold the top two spots.
  

Behind the news: OpenAI called DevDay 2026 its biggest yet, with more than 20 announcements, and cited 1.2 billion weekly users.

• Dots are autonomous agents comparable to OpenClaw or Meta’s Muse. Like Muse, each Dot has its own cloud computer and browser and can connect to more than 4,000 apps through OpenAI’s plugins. Users can message or call their dots in ChatGPT and message them in Slack or Microsoft Teams. Dots learn a user’s preferences from feedback over time. Users can also write rules that govern which actions a Dot may take on its own and which need approval or are off-limits. Certain sensitive tasks, such as changing a password, can only be authorized by a user. Dots are rolling out to ChatGPT Pro and Business Premium subscribers in eligible markets. Enterprise, Edu, and Healthcare workspaces can try a beta if an admin turns it on.

• Besides GPT-6.1 Sol and Dots, OpenAI announced (i) Ultrafast, a premium speed tier that, according to OpenAI’s DevDay recap, generates tokens up to 8 times faster (300 tokens per second) in Codex and up to 6 times faster via the API; (ii) Pro 500, a $500-per-month ChatGPT plan with 25 times the usage allowance of ChatGPT Plus and access to Ultrafast; and (iii) an app marketplace for enterprise customers to use their token plans for applications that integrate with ChatGPT.

What didn’t ship: GPT-6 Astra, which OpenAI released September 3, won’t get a matching upgrade for now. The day before DevDay, The Wall Street Journal reported that OpenAI had canceled the planned October release of GPT-6.1 Astra. In internal tests, the model showed more deception than GPT-6 Astra, including inaccurate accounts of which actions it had taken, and it sometimes pressed ahead with tasks without asking permission. OpenAI hopes to reuse GPT-6.1 Astra’s base model for reinforcement learning of future GPT-6 models.

Why it matters: Agents, which loop through many steps, reread long contexts, and work without supervision, stand to benefit most from GPT-6.1 Sol’s performance-to-price ratio and model guardrails. But that puts much of the weight on the guardrails around them. Given all this, it’s somewhat surprising that Dots don’t run on GPT-6.1 Sol, but the somewhat older and more expensive GPT-6 Astra.

We’re thinking: OpenAI says it held back GPT-6.1 Astra because the model didn’t meet its own security bar, even though that meant scrapping an October launch. Artificial Analysis published its own measurements of GPT-6.1 Sol the day it debuted. But Dots, which connect to users’ apps and act around the clock, have no comparable outside yardstick yet. We’d like to see independent testers put Dots and their agentic rivals through more rigorous tests of their security and capabilities like those that appeared to have stopped the release of GPT-6.1 Astra.

Argon, a Low-Hallucination Model Built for Knowledge Work

Google took over half a year before it replaced its flagship AI model, Gemini 3.1 Pro Preview. Now as then, the company’s latest release is among the leaders, but only cybersecurity defenders can use it for now.

What’s new: Google announced Gemini 4 Argon, a vision-language model trained to solve long, complex problems in software engineering, law, finance, and cybersecurity.

• Input/output: Text, images, and video in (up to 1 million tokens), text out (up to 1 million tokens)

• Features: Adjustable reasoning

• Performance: Leads Vals AI’s Vals Index v2.1 (68.9 percent); ties for third on Artificial Analysis’ Intelligence Index v4.3.2 (53)

• Availability: Currently only available to organizations in Google’s Fairwind cybersecurity program

• Price: Via API at an introductory price of $2/$0.10/$10 per million input/cached/output tokens, then $4/$20 per million input/output tokens

• Weights/license: Proprietary

• Undisclosed: Parameter count, architecture, latency and throughput, training data and methods, knowledge cutoff, end date of introductory pricing, date for broader availability

How it works: Google described how the model generates very long outputs and how it built safeguards around the model’s scientific and cybersecurity outputs.

• Gemini 4 Argon’s generations can extend up to 1 million tokens (up from 64,000 for Gemini 3.1 Pro Preview). This relies on a Gemini API feature called Long Decode Continuation, which pauses long responses and resumes them in later calls so requests don’t time out.

• Selected defenders in the company’s Fairwind Program and Google’s internal teams receive a version of the model without cybersecurity guardrails. Google says the version for wider release refuses harmful requests related to cyber, chemical, biological, radiological, or nuclear attacks.

• Google says it isolates and seals the environments it uses for high-risk training and evaluation. Last month, Google and security firm Irregular confirmed that during autonomous testing, an unnamed Gemini model was able to hack into three other companies’ systems due to poor sandboxing.

• Google uses inexpensive classifiers called probes to monitor the model’s internal activations, rather than its text output, for signs of disallowed uses, a technique it used in earlier Gemini models.

• To defend against indirect prompt injections (instructions hidden in documents or web pages the model reads), Google synthetically generated many such attacks and trained the model to resist them.

• Monitors read the model’s reasoning and actions and halt operations when they stray beyond Google-defined parameters. Similar systems monitored training. Google kept these systems’ findings out of the training set so the model wouldn’t learn to hide its reasoning from them.

Performance: Independent benchmarks rank Gemini 4 Argon well above Google’s other models and near the top of the field. It leads most tests of finance, legal, and business performance and seldom guesses wrong when it doesn’t know an answer. It still trails Anthropic’s newest models on agentic coding and Artificial Analysis’ broad index of overall intelligence.

• On Vals AI’s Vals Index, eight finance, coding, legal, and tax benchmarks weighted by each sector’s share of U.S. gross domestic product, Gemini 4 Argon set to high reasoning ranks first of 43 models (68.9 percent accuracy, $15.68 and 46.55 minutes per test at standard prices).

• On Artificial Analysis’ Intelligence Index, a composite of 10 evaluations across math, science, coding, and reasoning, Gemini 4 Argon set to high reasoning (53, $1.99 per task at discounted price, $3.98 per task at standard price) achieves the same overall score as GPT-6 Astra set to max reasoning and Claude Fable 5.1 set to max reasoning with fallback at lower cost per task.

• On AA-Omniscience, a test of factual knowledge that penalizes wrong answers but not refusals, Gemini 4 Argon set to high reasoning has the lowest hallucination rate (15 percent) of any model scoring 45 or higher on the Intelligence Index, significantly lower than other flagship models, such as GPT-6 Astra set to max reasoning (51 percent).

• On Arena.ai’s Text Arena leaderboard, which ranks models via blind head-to-head comparisons, Gemini 4 Argon set to high reasoning ranks first (1,525 Elo), ahead of Claude Opus 4.6 set to high reasoning (1,505 Elo) and Claude Opus 5.5 set to high reasoning (1,504 Elo).

Behind the news: Anthropic and OpenAI frequently release new models, particularly those they believe could pose a cybersecurity risk, only through gated programs (and for internal use). With Gemini 4 Argon, Google follows their example. In each case, organizations selected by the AI company get a less-restricted version first, and everyone else gets a version with more safeguards later.

• Anthropic initially limited all its Mythos models to members of Project Glasswing, its organization of U.S. cybersecurity and life sciences organizations that do defensive work. Only selected companies can use Claude Mythos 5.1, while anyone can use Claude Fable 5.1, which includes safeguards and retains input data for one month.

• OpenAI’s Daybreak program sorts selected organizations that do defensive cybersecurity work into tiers. Besides OpenAI itself, only one tier, Daybreak Red, can use GPT-6 Astra with reduced safeguards. Other customers get a model with limits.

• Google used this approach with its Fairwind Program and Gemini 3.8 Flash Cyber, a variant of Gemini 3.8 Flash with looser cybersecurity safeguards that only selected cybersecurity organizations can use.

Why it matters: One of Gemini 4 Argon’s strengths is long-context and high-output code migrations. Google said its agents translated C and C++ code into Rust across the company, including more than 800,000 lines from the kernel of Fuchsia, an open-source operating system that Google developed. Rust is designed to prevent many of the memory bugs that C and C++ allow. A patch fixes one vulnerability, but a rewrite in Rust addresses an entire vulnerability category. If models like Gemini 4 Argon can enable such rewrites quickly and cheaply, defenders may be able to remove specific types of vulnerabilities before attackers find them, rather than patching them piecemeal.

We’re thinking: Many models are competing to be the best software engineering assistant in the world. Gemini 4 Argon may not be the most powerful coder, but Vals AI’s index shows its strengths in fields like finance, taxes, and law. Gemini 4 Argon is also the frontier model most likely to admit it doesn’t know the answer to a factual question rather than guess wrong. In a financial analysis or legal brief, a confident incorrect answer may slide past a reviewer, while a refusal is obvious and can be passed to a person or another model — assuming applications using it have a plan for questions the model won’t answer.

What Else Happened in AI on October 09th 2026?

President Trump called those who refuse to call AI “Super Intelligence” “THE ENEMY,” following his executive order officially directing federal agencies to adopt the term.

Independent researcher Pavel Rabtsevich used Claude Code and Codex to identify a potential new planet hidden in NASA telescope data dating back to 2018.

Anthropic launched Claude Dashboards and Motion, letting users turn their data into interactive dashboards and prompts into editable, animated explainers.

Anthropic also launched OSS Scanner, a free service that uses its strongest models, Mythos included, to scan open-source projects for vulnerabilities and suggest fixes.

The Association for Human Mathematics condemned OAI’s 700+ mathematical documents as a show of “power,” urging researchers to stop working with the company.

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