Tech
IBM makes developing for quantum computers easier with the Qiskit Functions Catalog
IBM today launched the Qiskit Functions Catalog, a new set of services that aims to make programming quantum computers easier by abstracting away many of the complexities of working with these machines.
“I do think it’s the next big transition ince we put the quantum computer on the cloud,” Jay Gambetta, IBM’s VP in charge of its quantum programs, told me. “I’m looking forward to seeing what it can do and the only way that’s possible is with performant hardware, of course, but also performant software. To me, I’m as excited as when I put the quantum computer on the cloud to see how the community will react to it.”
Quantum computers continue to get bigger and better (and more error-corrected). And while we’re still at least a few years out from having machines that can run algorithms that would take impossibly long to compute on a classical computer, we are at a point where the current generation of machines is usable for at least a limited set of experiments. It’s one thing to have usable hardware, though. It’s another to write applications for that hardware.
Launched in 2017, IBM’s Qiskit is one of a handful of quantum programming frameworks that also include Microsoft’s Q# and Google’s Cirq, but it’s likely the one with the largest mindshare. The idea behind the Functions Catalog to enable domain experts — who may not be experts in managing quantum computers and their fickle ways — to start using quantum computing. A company like Qedma, for example, is putting its novel way of doing error mitigation into a function.
And that’s IBM’s overall approach here: work with the wider quantum computing industry to create this library of functions that, just like in programming a classical computer, developers can then call upon in their Qiskit-based applications. Other partners include Q-CRTL, Algorithmiq, and Qunasys. Like Qedma, Algorithmiq is contributing a service that focuses on error mitigation in noisy systems, while Qunasys is offering a service that aims to solve the ground state energy estimation problem, which has some fundamental applications for chemistry-related problems.
“What has driven the progress of software and compute in the classical world of abstraction is becoming a reality in the quantum world,” Gambetta said. Not many developers today, after all, focus on writing assembly. Yet in quantum computing, it’s not that long ago that developers had to figure out how to map their algorithms to quantum circuits for a specific target hardware. The Qiksit framework already abstracted much of this away and now the Functions Catalog aims to make it easier for non-quantum computing experts to take many of the innovations in the overall ecosystem and apply them to their problems.
“I think this is going to be as big as when we put the computer on the cloud because it’s going to transition everyone from having to learn what a quantum gate is and quantum circuits to ‘can I actually start to see how quantum computing will be injected into my workflow? And I don’t need to worry about these details. And this is just the start,” Gambetta said. He also stressed that it’s the continuous innovation in software and hardware, combined with the innovations from the larger partner ecosystem, that will bring a simplified developer experience to users that will, eventually, unlock quantum computing’s potential.
Now, Gambetta stressed that we’re not yet at the point where the company is targeting enterprise developers. “It’s gone from the physicist, to the computational scientist, to the chemist. […] It’s opening the aperture to really allow computer scientists to come in and to increase the technical breadth of what can be done with the quantum computer,” he said.
As part of today’s announcement, IBM is also launching Benchpress, a set of new benchmarks for quantum software development kits. Using over 1,000 tests (with only a handful written by IBM itself), IBM pitted Qiskit against BQSKit, Braket, Cirq, Stak and TKET. Qiskit, which IBM has been rewriting in Rust to make it more performant, typically outperforms the other SDKs by a wide margin. It was 13 times faster and transpiling and producing circuits, for example, and also created more efficient circuits in the process.
Tech
Exclusive: Google deepens Thinking Machines Lab ties with new multi-billion-dollar deal
Former OpenAI executive Mira Murati’s startup, Thinking Machines Lab, has signed a new multi-billion-dollar agreement to expand its use of Google Cloud’s AI infrastructure, including systems powered by Nvidia’s latest GPUs, TechCrunch has exclusively learned.
The deal is valued in the single-digit billions, according to a source familiar with the matter, and includes access to Google’s latest AI systems built atop Nvidia’s new GB300 chips, alongside infrastructure services to support model training and deployment.
Google has been actively striking a number of cloud deals with AI developers as it aims to wrap together its AI computing offerings with other cloud services like storage, a Kubernetes engine, and Spanner, its database product. Earlier this month, Anthropic signed an agreement with Google and Broadcom for multiple gigawatts of tensor processing unit (TPUs) capacity (these are Google’s custom-designed AI chips for machine learning workloads).
But the competition is fierce. Just this week, Anthropic also signed a new agreement with Amazon to secure up to 5 gigawatts of capacity for training and deploying Claude.
Earlier this year, Thinking Machines partnered with Nvidia in a deal that included an investment from the chipmaker. But this is the first time the lab has struck a deal with a cloud services provider. The deal is not exclusive, so Thinking Machines may use multiple cloud providers over time, but it’s still a sign that Google is looking to lock in fast-growing frontier labs early.
Murati left her job as OpenAI’s chief technologist and founded Thinking Machines in February 2025. The company, which soon afterwards raised a $2 billion seed round at a $12 billion valuation, has remained highly secretive, but launched its first product in October. Dubbed Tinker, it’s a tool that automates the creation of custom frontier AI models.
Wednesday’s deal provided some insight into what Thinking Machines is developing. In a press release, Google noted that it can support the startup’s reinforcement learning workloads, which Tinker’s architecture relies on. Reinforcement learning is a training approach that has underpinned recent breakthroughs at labs, including DeepMind and OpenAI, and the scale of the Google Cloud deal reflects how computationally expensive that work can get.
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Thinking Machines is among the first Google Cloud customers to access its GB300-powered systems, which offer a 2X improvement in training and serving speed compared to prior-generation GPUs, per Google.
“Google Cloud got us running at record speed with the reliability we demand,” Myle Ott, a founding researcher at Thinking Machines, said in a statement.
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Tech
The most interesting startups showcased at Google Cloud Next 2026
Google Cloud Next is taking place this week in Las Vegas, and one clear message has emerged: Google wants AI startups on its cloud. To that end, it made several startup-related announcements.
The most significant is that the tech giant has earmarked a new $750 million budget to help its Cloud partners sell more AI agents to enterprises. This funding is available to partners ranging from startups to the big consulting firms. It can be used for costs like Gemini proof-of-concept projects, Google forward-deployed engineers, cloud credits, and deployment rebates.
Google also highlighted a long list of startups that are using Google Cloud, either newly signed or expanding their footprint. Among them are a few standout names:
Lovable is expanding its use of Google Cloud by launching a new coding agent through Google’s enterprise app marketplace. Lovable is the fast-growing vibe coding startup and was on a $400 million ARR track as of February, it said.
Notion, Silicon Valley’s favorite AI-infused document productivity app, most recently valued at about $11 billion, is using Gemini models to power its text and image generation features.
Gamma, an AI-powered PowerPoint killer recently valued at a $2.1 billion valuation, is using Google’s state-of-the-art image model Nano Banana 2 and other Google Cloud features.
Inferact, the commercial inference startup from the creators of the popular open-source project vLLM, is accessing Nvidia’s GPUs through Google Cloud, in addition to using the tech giant’s AI stack.
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ComfyUI, the popular open-source tool for creating AI-generated images and multimedia, also offers access to Nano Banana 2 and is using other Cloud features.
Other startups that received the Google Cloud shout-out this year include:
ChorusView, which makes AI-powered smart tags that track the condition and movement of goods in real time.
Emergent AI, a vibe coding platform.
ExaCare AI, which makes AI software for post-acute medical care facilities.
Insilica, which creates AI-generated regulatory-compliant chemical safety reports.
Optii, which makes AI-enhanced hotel operations software.
Parallel AI, which builds web search and research APIs built for AI agents.
Proximal Health, which makes AI-powered software that automates the insurance claims adjudication process.
Reducto, which does AI-powered document parsing.
Stord, which handles e-commerce fulfillment and parcel operations.
Stylitics, which makes AI image generation software for retailers for tasks like outfit styling and product bundles.
Temporal, a developer cloud environment built to prevent failures.
Vapi, which makes dev tools for building conversational voice agents.
Vurvey Labs, which conducts synthetic market research via AI agents.
Wand, an in-game assistant for single-player PC games.
Watershed, which makes software that helps enterprises report on and manage sustainability programs.
ZenBusiness, an all-in-one back-office tool for small businesses that includes an AI chat assistant.
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Tech
Duolingo is now giving free users access to advanced learning content
Duolingo announced on Wednesday that its advanced language learning content is now available for free across nine languages: English, Spanish, French, German, Italian, Portuguese, Japanese, Korean, and Chinese. Users can access this content through the web, iOS, and Android devices.
This advanced content is at the B2 level on the Common European Framework of Reference for Languages (CEFR), which is the international standard for language skills that schools and employers recognize. B2 level content refers to learning materials without translations, complex scenarios, and specialized vocabulary.
The new offering will include features like “Advanced Stories,” which helps with reading comprehension, and DuoRadio, a podcast-like audio experience for listening comprehension.
Now that Duolingo users can tap into this advanced learning content for free, they can level up their skills, whether that’s practicing for job interviews, prepping for studying abroad, or tackling complex news articles, films, and books without relying on translations.
The company says this positions it as the only free app to offer advanced-level learning across these nine languages at no cost. While competitors like Babbel and Busuu offer advanced courses, they typically require paid subscriptions. For instance, Busuu has some CEFR-aligned courses up to the B2 level, but the free version is pretty limited and doesn’t offer lessons like grammar explanations, so users need to pay for full access.
Previously, Duolingo only provided free courses that capped at A2 or B1 levels, mainly focusing on basic communication skills.
The company is positioning this free advanced learning offering as an enticing opportunity for job seekers, framing language learning as a practical pathway to improving employability in an increasingly global workforce.
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This comes at a time when the job market remains highly competitive and overall growth has slowed. Research from the American Council on the Teaching of Foreign Languages shows that learning a second language can raise someone’s employability by as much as 50%.
“Reaching job-ready proficiency in a new language used to be out of reach for most people,” Bozena Pajak, head of learning science at Duolingo, said in a statement. “It took years of expensive classes or immersive experiences that not everyone could access.”
Duolingo’s decision to offer advanced learning for free is also a strategy to increase its free user base. In its Q4 earnings report, the company stated that it has 52.7 million daily active users, demonstrating 30% growth compared to the previous year. This number is higher than its paid subscriber base, which stands at 12.2 million. However, Duolingo’s shares fell after the company projected that the year-over-year bookings growth rate for Q2 2026 is expected to experience a slight decline.
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