Sep 15, 2026 · 5 min listen · Last updated September 15, 2026
From storyflo. This is your daily audio brief. It's Theo. September 15th, tech roundup — five stories, here's number one. Let's get into it. First, from TechCrunch AI. OpenAI, Anthropic, Google have been in talks on AI safety for weeks.
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OpenAI, Anthropic, Google have been in talks on AI safety for weeks
Chris Lehane, OpenAI’s global policy chief, told reporters on Tuesday that the company has been working with rivals Anthropic and Google DeepMind on AI safety for weeks, as first reported by Bloomberg. Lehane is reportedly in Washington to work with U.S. lawmakers addressing catastrophic risks associated with AI. The revelation comes in the wake of Anthropic CEO Dario Amodei’s essay, published Saturday, which called for the industry to work together to slow the pace of frontier AI and avoid catastrophic risks.
Apple brings a fully revamped Siri built on Google's Gemini, but not to the EU
Apple is shipping its rebuilt "Siri AI" after years of delay, built on Google's Gemini models and running partly on the device, partly through Private Cloud Compute. Early testers praise multi-step requests and screen context, but report hallucinations and gaps with personal context. In the EU, the assistant stays unavailable for now. The article Apple brings a fully revamped Siri built on Google's Gemini, but not to the EU appeared first on The Decoder.
5 Free Microsoft GitHub Courses to Learn Data Science and Artificial Intelligence
Explore five free Microsoft GitHub courses covering data science, machine learning, artificial intelligence, generative AI, LLMs, RAG, fine-tuning, and AI agents. You do not need expensive courses to learn data science and artificial intelligence. Microsoft has created several complete, free learning curricula on GitHub with lessons, quizzes, assignments, code examples, and projects. AI learning has also expanded far beyond traditional data science and machine learning.
How I’m Using Google Opal for Even More AI Automations
Opal is Google Labs' no-code tool for turning natural language into working AI mini-apps, built on top of an internal framework called Breadboard. Here's how I learned to use it best. The last time I opened Opal to start a new build, something in the interface had quietly changed. The Generate step, the one I'd used a dozen times to pick Gemini or Imagen or Veo, now had a new option sitting right above the familiar model list, simply labeled "Agent." No blog post had landed in my inbox announcing it. It was just there, waiting to be clicked.
- India’s creative industry is using AI at a higher rate than the rest of the world, with arts, design, and media occupations making up 19% of work-related AI usage, 1.6 times the global average. - The U.S. is leading in technical AI adoption, with computer and mathematical occupations accounting for 30% of work-related AI usage, double the share in the rest of the world. To make these insights and ATLAS's millions of other global data points easier to explore, we're launching a new interactive, open-access experience.
When Jessica Wachter, a finance professor at the University of Pennsylvania’s Wharton School, wanted to assess AI’s impact on the economy over the next few years, she faced a long list of business and technical uncertainties. So she started with what she calls a “remarkable fact” that is not in question: A handful of so-called hyperscalers are investing huge amounts of money to build AI data centers.
Agility Robotics says its new Digit 5 robot can work next to people without safety fences
Agility Robotics has unveiled Digit 5, the next version of its humanoid robot for warehouses and factories. The article Agility Robotics says its new Digit 5 robot can work next to people without safety fences appeared first on The Decoder.
After warning AI is too dangerous, Bill Gates bets a billion on its upside
The Gates Foundation is investing at least a billion dollars over two years to make AI tools more widely available in health, education, and agriculture. Bill Gates warns that more than 90 percent of the training data behind early language models came from English sources, and that speech recognition fails 60 percent of the time in Yoruba. The market, he says, is "a terrible guarantor of equal opportunity." The article After warning AI is too dangerous, Bill Gates bets a billion on its upside appeared first on The Decoder.
How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It.
Before reaching for an LLM API on every classification problem, it's worth knowing what a decades-old baseline can already do with the labeled data you have — and exactly how much more data buys you. The post How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It. appeared first on Towards Data Science.
How statistical moments connect the mean, the variance, and higher powers of a distribution If you’ve spent any time in statistics or machine learning, you’ve met the usual suspects: the mean and the variance. If you're feeling brave, you might even look at skewness or kurtosis. In day-to-day data analysis, it is easy to treat these metrics as a disjointed collection of individual tools — a patchwork utility belt of sorts.