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Matthias Bastian

Matthias is the co-founder and publisher of THE DECODER, exploring how AI is fundamentally changing the relationship between humans and computers.

OpenAI decides the best way to fight critical AI coverage is to own a newsroom

OpenAI has acquired tech talk show TBPN. The show will supposedly remain editorially independent but report to OpenAI’s communications department. That’s as contradictory as it sounds. So what’s OpenAI really after?

Read full article about: Sakana AI launches "Ultra Deep Research" to automate weeks of strategy work

Japanese AI startup Sakana AI has unveiled "Sakana Marlin," its first product for business customers. The system works autonomously: give it a topic, and it researches on its own for up to eight hours, then delivers detailed reports and presentations. Sakana AI says the tool can produce professional strategy analyses that would normally take human teams several weeks.

Eine Übersichtsansicht eines von der KI generierten Beispiel-Dokuments. Zu sehen sind mehrere hochformatige Textseiten eines Berichts sowie darunterliegende querformatige Präsentationsfolien in japanischer Sprache. Auf dem Deckblatt sind das Logo von Sakana AI, der Name „Sakana Marlin“ sowie das Wasserzeichen „Sample output“ zu erkennen.
Sample output from "Sakana Marlin": after autonomous research, the tool creates text reports and presentation slides on a given topic (here: AI trends in the financial sector). | Image: Sakana AI

Sakana Marlin combines the company's "AI Scientist," designed to resolve contradictions, with its previously introduced "AB-MCTS" method for strategic searches. Multiple AI models work together, and longer thinking time is meant to yield better results, the company says.

The company is looking for beta testers in finance, research, and business consulting. The beta is free, but requires registration (the form is in Japanese). The biggest weakness of automated reports like these is hard-to-spot AI errors, something the startup doesn't address in its announcement.

Read full article about: Microsoft's MAI-Transcribe-1 runs 2.5x faster than its predecessor at $0.36 per audio hour

Microsoft has introduced MAI-Transcribe-1, a speech-to-text model supporting 25 languages that achieves the lowest word error rate of any model tested on the FLEURS benchmark, beating Scribe v2, Whisper-large-V3, GPT-Transcribe, and Gemini 3.1 Flash-Lite. The model is also built to handle tough recording conditions like background noise, poor audio quality, and overlapping speech, Microsoft says.

MAI-Transcribe-1 (green) leads in word error rate on the FLEURS benchmark in most of the 25 languages tested, outperforming Scribe v2, Gemini 3.1 Flash-Lite, Whisper-large-v3, and GPT-Transcribe. | Image: Microsoft

Microsoft is rolling out MAI-Transcribe-1 across Copilot Voice and Microsoft Teams. Developers can try it as a public preview through Microsoft Foundry and the Microsoft AI Playground. The model runs 2.5 times faster than Microsoft's previous Azure Fast offering and costs $0.36 per audio hour. Combined with MAI-Voice-1 and a language model, it can also power voice agents, Microsoft says.

Cohere and Mistral recently released open-source alternatives that perform at a similar level.

Read full article about: Anthropic's leaked AI coding tool has been cloned over 8,000 times on GitHub despite mass takedowns

Following the accidental leak of its AI coding tool's source code, Anthropic has had more than "8,000 copies and adaptations of the raw Claude Code instructions" removed from GitHub via a copyright request, the Wall Street Journal reports. One programmer already used AI tools to rewrite the code in different languages, keeping it available despite takedowns. This shows just how damaging a code leak is in the age of AI: once it's out, it spreads faster than anyone can contain it.

The code contains valuable techniques Anthropic uses to control its AI models as coding agents—the "harness"—including a "dreaming" function for task consolidation. Competitors now have a blueprint to replicate Claude Code's capabilities, weakening Anthropic's edge in an already cutthroat market.

The timing is particularly bad: the company is planning an IPO at a $380 billion valuation, and this kind of leak is unlikely to sit well with investors. It also comes just days after a separate leak about Anthropic's new AI model Mythos, also caused by human error within the company's content management system.

Comment Source: WSJ

Google Deepmind study exposes six "traps" that can easily hijack autonomous AI agents in the wild

AI agents are expected to browse the web on their own, handle emails, and carry out transactions. But the very environment they operate in can be weaponized against them. Researchers at Google Deepmind have put together the first systematic catalog of how websites, documents, and APIs can be used to manipulate, deceive, and hijack autonomous agents, and they’ve identified six main categories of attack.

Read full article about: OpenAI officially confirms mega-funding round and ChatGPT super app

OpenAI has officially closed its latest funding round. The company raised $122 billion at a valuation of $852 billion. Key backers include Amazon, Nvidia, SoftBank, and Microsoft, along with a16z, BlackRock, Sequoia Capital, and several other investors. Private investors put in $3 billion through banking channels, and the company also expanded its credit line to $4.7 billion.

OpenAI says it's now pulling in $2 billion in monthly revenue and has crossed 900 million weekly active ChatGPT users. The company also officially unveiled the ChatGPT Super App, a single product that rolls together ChatGPT, the Codex coding agent, web search, and what OpenAI describes as "our broader agentic capabilities into one agent-first experience."

The bulk of the new capital will go toward computing infrastructure. OpenAI is clearly leaning harder into enterprise going forward; the company recently killed off its Sora video model to free up compute and because it wasn't gaining traction anyway. Enterprise already accounts for more than 40 percent of the company's total revenue. "Our consumer scale becomes the front door for enterprise usage, as familiarity in daily life drives adoption at work," OpenAI writes.