DualChem, a new benchmark from @scale_AI, tested 29 frontier models on dual-use chemistry questions: ones that could serve either legitimate scientific research or harmful ends. They frequently flagged the risk, then answered anyway. Recognition is not refusal. DualChem is part of our research collaboration with @NIST’s Center for Advancing Innovation and Standards for Super Intelligence (CAISSI). Governments need independent testing capacity they don’t have today. @madialder covered the findings at FedScoop:

NEWS: @scale_AI is putting down roots in Qatar. Today we signed an agreement with @UDCQatar to establish a long-term home in Doha. Our team in Doha has grown to nearly 100 people. The office at The Pearl builds on our five-year partnership with @MCITQatar, where our team is making healthcare, justice, education and tourism services more reliable for the people who depend on them. We’ve also trained nearly 6,000 government employees. Qatar’s AI ambitions depend as much on its people as on its technology, and building that literacy and confidence matters as much as anything we deploy. Thank you to MCIT for its leadership, and to UDC for helping us build a lasting home.

From the beginning, Scale was built by people who love solving hard problems. That same ambition is driving what we build next. Our ML Research Internship Program is accepting applications in SF and NYC. Work on frontier AI research alongside @ScaleAILabs researchers, publish your work, and help build the next generation of AI. Apply now.

NEWS: Scale is open for business in the UAE! Today at the Dubai AI Festival, we launched Scale AI in the UAE. Between this launch and our partnership with @PresightAI, we’re moving quickly to support the UAE’s national investment in AI.  Our role in this part of the world is to help these institutions put their strategy into practice by standing up AI that works reliably in Arabic, meets local governance requirements, and keeps people in control. Our UAE team is based at the Dubai International Finance Center - thank you to the @DIFC for the warm welcome. We’re excited to be part of UAE’s dynamic AI industry.

Nemotron 3.5 Bolt E4B 4GB is an impressive small language model. Its 76.8% on instruction retention shows it’s already strong out of the box, giving builders a solid base for post-training. Congrats to @JensenHuang and the @NVIDIAAI team on the launch.

At #NVIDIAGTC# Berlin, @JensenHuang highlighted our work with @Skydance to post-train @NVIDIAAI Nemotron 3.5 Super VL. On real production tickets, the agent matched frontier-model accuracy at ~1/40 the inference cost and 5x the speed.

Scale ❤️ NVIDIA: Proprietary data + great post-training = sovereign intelligence. Thanks @JensenHuang and @nvidia for highlighting what @scale_AI and @Skydance built on Nemotron: +15 pts in accuracy.

From classrooms to legislative drafting, AI is being built into specialized government workflows. Through a multi-year partnership with @MCITQatar, Scale is one of the partners contributing to AI adoption across Qatar’s public institutions. What that looks like in practice ↓

The future of enterprise AI is multi-model, and enterprises deserve the freedom to choose. NEWS: We’re expanding that choice through our collaboration with @NVIDIA, post-training its open-weight Nemotron 3.5 Super VL for enterprise workflows. Here’s what it delivered for two of our customers: ✅ @Skydance: A complex finance workflow that reviews vendor credit memos, statements and invoices to find credits the company is owed. Post-trained Nemotron matched their current frontier model’s accuracy at 40x lower inference cost, with 5x faster response times. ✅ @EY_US: An M&A due diligence agent that finds and reconciles answers across hundreds of files in a virtual data room. Post-trained Nemotron matched EY’s current frontier model at about one-eighteenth of the inference cost, returning answers more than twice as fast. Put NVIDIA’s open-weight models to work for your business with Scale Post-Training. Thank you, @JensenHuang and the NVIDIA team, for the early access and collaboration.

A great pianist can play almost anything, but mastering one piece is what makes a performance exceptional. The same goes for AI. With today's launch of Nemotron 3.5 Super VL, we’re collaborating with @NVIDIAAI to combine their open post-training tools with Scale’s data, evaluation and applications building expertise. Together, we're turning general-purpose models into powerful, cost-effective specialists for enterprises everywhere. Welcome to the multi-model world. 🤝

People increasingly turn to AI chatbots for mental health support. But are models actually helping when it matters most? We're releasing DistressBench, a new benchmark measuring how well AI models respond to mental health crises.

We’re introducing Humanity’s Sixth Sense, a new benchmark testing the intuitive visual reasoning people rely on every day. Across 522 open-ended tasks spanning images and video, HSS tests everything from spatial and causal reasoning to social understanding. The gap is significant. Humans score 93.1%, while the strongest model, GPT-6-astra, reaches 53.6%. The median model scores just 30.9%.

Much of the AI security debate is about frontier models. But a lot of people are building on open-weight models. We need to understand their capabilities and risks too. A real testing strategy covers every model, not just the frontier.

You can’t improve agents if you can’t measure where and why they fail. At #LATechWeek#, we're hosting a hands-on evals workshop led by our Head of General Agents @Bckenstler to break down how we structure evals, what we measure, and how we use the results to improve AI systems. Apply here to join us:

We’re excited to bring @nvidia's Open Agent Safety Platform technologies to Scale GenAI Portfolio, helping us build, train, deploy, run, and evaluate AI agents in controlled environments with enforceable security and a clear record of their actions.

The nation that can measure the AI frontier will be the one that steers it. Our future should not be steered by speculative warnings. We have to be driven by evidence. That was the clearest takeaway from this week's AI conversations at the UN General Assembly. Governments need to get serious about testing frontier AI, and nowhere is that more urgent than in Washington. Getting serious means three things: → Clear responsibility for testing across agencies → Access to models before they're deployed → Funding for the experts and tools to do the work Scale AI's cyber research shows what testing can reveal. We've seen AI agents carry out an attacker's instructions while still finishing the user's task, so the user never knew anything went wrong. We've also seen models refuse to help people defend their own systems. Both are failures. Real testing has to measure the harm AI can cause and the help it fails to give. Government shouldn't have to rely solely on AI developers to explain these failures. It needs its own testing capacity, with the expertise to ask hard questions and the tools to answer them. Scale has worked with the U.S. government for years to test the risks and capabilities of AI models, and we're accelerating that work in the months ahead. Here's what we think America should do next: