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New usage analytics and updated spend controls for enterprises

Data & Analytics

New usage analytics and updated spend controls for enterprises

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New usage analytics and updated spend controls give ChatGPT Enterprise admins more visibility, control, and confidence in their AI deployments. As AI becomes part of everyday work, organizations need the ability to manage it with the same rigor they apply to any critical business investment. Companies need a clear view of usage, adoption, and spend so they can scale with confidence and understand where AI is creating value. Today, we’re introducing credit usage analytics and updated spend controls for ChatGPT Enterprise. These capabilities help companies track credit usage, understand adoption…

OpenAI · 18 Jun 2026 · 19:00 CESTRead story →Original ↗
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Healthcare

Improving health intelligence in ChatGPT

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GPT‑5.5 Instant brings frontier health intelligence to more people, shaped by advances in our models and physician-led evaluation. Health is one of the most meaningful ways people use ChatGPT. Every week, more than 230 million people turn to ChatGPT for help with health and wellness questions: making sense of health information, understanding lab results, preparing for appointments, navigating insurance, building healthier habits, and figuring out what to ask next. With GPT‑5.5 Instant, we’re seeing a substantial step forward in health, with improvements in recognizing when urgent care may be needed,…

OpenAI · 18 Jun 2026 · 13:00 CESTRead story →Original ↗
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Using AI to help physicians diagnose rare genetic diseases affecting children

Models & tools

Using AI to help physicians diagnose rare genetic diseases affecting children

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In an NEJM AI study, experts used an OpenAI reasoning model to reanalyze 376 previously unsolved cases and surface leads for 18 diagnoses. Even with genomic sequencing, many people with rare diseases never receive a clear genetic diagnosis. Roughly half remain undiagnosed after extensive testing and specialist review. Their medical data may contain clues but finding them can require sifting through thousands to millions of possible genetic variants, fragmented clinical records, and rapidly changing scientific literature. As new gene-disease relationships, case reports, and classification evidence accumulate, unsolved cases can become…

OpenAI · 18 Jun 2026 · 10:00 CESTRead story →Original ↗
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MIT in the media: For the future of tech, “Massachusetts can absolutely lead”

Unclassified

MIT in the media: For the future of tech, "Massachusetts can absolutely lead"

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On June 9, The Boston Globe released its 2026 “Tech Power Players” list, recognizing 50 influential local leaders in technology and business across Massachusetts. The list includes eight MIT affiliates including President Sally Kornbluth, Prof. Daniela Rus (director of CSAIL), Prof. Regina Barzilay, Prof. Yet-Ming Chiang, Prof. Max Tegmark, Ana Bakshi (executive director of the Martin Trust Center for MIT Entrepreneurship), Katie Rae CEO and Managing Partner of Engine Ventures), and Senior Lecturer Brian Halligan, along with a number of MIT alumni. In addition to recognizing individual leaders, the Power…

MIT News · 18 Jun 2026 · 06:00 CESTRead story →Original ↗
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A near-autonomous AI chemist improves a challenging reaction in medicinal chemistry

Research

A near-autonomous AI chemist improves a challenging reaction in medicinal chemistry

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With Molecule.one’s Maria, GPT‑5.4 found a surprising additive boosting Chan-Lam Coupling yields for over 80% of tested substrates. OpenAI’s work in science is motivated by a simple belief: advanced AI can become a powerful partner for scientists, helping them explore more ideas, connect distant concepts, design better experiments, and accelerate discoveries that benefit humanity. We have already shared early examples of models contributing to novel results in mathematics, including work on the unit distance problem⁠, in theoretical physics, through a new result on gluon amplitudes⁠, and in biology, where GPT‑5…

OpenAI · 17 Jun 2026 · 12:00 CESTRead story →Original ↗
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Introducing LifeSciBench

Research

Introducing LifeSciBench

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Agentic AI systems are becoming increasingly capable of performing scientific tasks. However, their usefulness to life science researchers depends on how well they handle the complexity of real research. That work rarely looks like a single fact-recall question or a clean prediction problem. Researchers interpret incomplete evidence, reconcile conflicting results, design difficult experiments, troubleshoot assays, evaluate translational risk, and decide what to do next under uncertainty. Current benchmarks do not fully capture these capabilities. Many life science evaluations focus on narrow domains or isolated skills, resulting in questions with structured…

OpenAI · 17 Jun 2026 · 02:00 CESTRead story →Original ↗
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Predicting model behavior before release by simulating deployment

Models & tools

Predicting model behavior before release by simulating deployment

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Using realistic conversation contexts to better estimate undesired model behavior before release. Before releasing a new model, labs need to understand not just what it can do, but how it is likely to behave in real-world use, including where it might introduce new risks. This becomes even more important as capabilities increase. As part of our pre-deployment safety review, we leverage targeted evaluations, red-teaming, and other checks to understand model behavior. We’ve now started using a method for simulating model deployments before they happen, which adds a complementary signal: a…

OpenAI · 16 Jun 2026 · 02:00 CESTRead story →Original ↗
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Business use

Introducing the OpenAI Partner Network

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The limiting factor for seeing value from AI in the enterprise is no longer model capabilities. Instead, it’s how organizations repeatably identify the right use cases, redesign workflows, integrate with existing systems, and drive adoption and change management at scale. Helping every organization adopt OpenAI frontier models and products and turn them into measurable impact requires an ecosystem of trusted partners with deep industry expertise, global delivery capacity, and customer relationships. Today, we’re announcing the OpenAI Partner Network to deliver just that. The OpenAI Partner Network is a new program…

OpenAI · 14 Jun 2026 · 19:00 CESTRead story →Original ↗
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Automation & Agents

New OpenAI Academy courses for the next era of work

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AI is giving organizations a new capacity to act. Work that once waited for scarce time or expertise can increasingly move forward with AI. But that promise only becomes real when people know how to apply these tools in the context of their work and turn successful uses into repeatable ways of working. At OpenAI, we view learning as part of deployment. We build the models and products and work closely with organizations applying them across their businesses. OpenAI Academy turns those insights into practical learning that helps organizations build…

OpenAI · 12 Jun 2026 · 12:00 CESTRead story →Original ↗
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Education

How Preply combines AI and human tutors to personalize learning

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Preply uses OpenAI to launch AI-generated lesson summaries, providing personalized feedback and language learning exercises. Preply⁠ is the world's largest marketplace for online language learning, connecting more than 100,000 expert tutors with learners across more than 180 countries. Through personalized one-to-one instruction across more than 90 languages, Preply’s mission is to make high-quality language education accessible to anyone, anywhere. Language learning is fundamentally human. It requires conversation, confidence, motivation and cultural understanding. While Preply tutors provide irreplaceable energy, motivation, cultural nuance, and human connection for learners, they also face repetitive…

OpenAI · 12 Jun 2026 · 02:00 CESTRead story →Original ↗
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Research

How an astrophysicist uses Codex to help simulate black holes

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Codex helps Chi-kwan Chan to refine and test algorithms that simulate the movement of electrons and ions around a black hole. The gravity around a black hole is so extreme that nothing, not even light, can escape once it gets close enough. Astrophysicists like Chi-kwan Chan study black holes with computer simulations and observations. But current algorithms and computing power limit how realistic those simulations can be. With Codex, Chan—a researcher at the University of Arizona and Steward Observatory—is tackling this problem. Black holes are among the best places to…

OpenAI · 11 Jun 2026 · 02:00 CESTRead story →Original ↗
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