MTS @MicrosoftAI Superintelligence | PhD in StatML @UniofOxford @oxcsml | Prev @MSFTResearch @AmazonScience @imperialcollege | (Probabilistic) Generative Models
Cambridge, UK
Joined March 2016
- Tweets155
- Following1K
- Followers498
- Likes719
Pinned Tweet
Introducing the Analog Optical Computer (AOC) 💻 which computes matrix-vector products and non-linearities with light💡and analog electronics⚡ instead of bits at incredible speed, and with the potential to be 100x more energy-efficient than GPUs at scale. Now out in @Nature .
Our breakthrough work on an analog optical computer points to new ways to solve complex real-world problems with much greater efficiency. Super to see this published today in @Nature. news.microsoft.com/source/fe…
We're announcing MAI-Base-2! I feel incredibly fortunate to have contributed to this as part of the amazing pretraining team at MAI. And we're hiring, come join us on our path to the frontier!
microsoft.ai/careers/
We now have state-of-the-art pre-trained base models in the 3T-parameter weight class, built entirely in-house at MAI.
Post-training results coming soon -- stay tuned!
Lots of details in our technical blog post.
microsoft.ai/news/frontier-p…
Fabian Falck retweeted
We are #1 on image editing on AA!
What a nice surprise. Thanks AA for help with benchmarking!
Microsoft's MAI-Image-2.5-Pro debuts at #1 on the Artificial Analysis Image Editing Leaderboard, and takes the #7 spot in Text to Image
MAI-Image-2.5-Pro is Microsoft AI's quality-focused image model, launched July 23 in preview on Microsoft Foundry. It joins MAI-Image-2.5 and MAI-Image-2.5-Flash in a family Microsoft positions as covering the quality-speed-cost curve, so builders can pick the point that fits their job. Pro sits at the quality end: Microsoft describes it as its highest-fidelity image model to date, aimed at hero imagery, detailed editing, and precise in-image text rendering.
In the Artificial Analysis Image Arena, MAI-Image-2.5-Pro debuts at #1 on the Image Editing Leaderboard, surpassing Reve 2.1, GPT Image 2, and Microsoft's own MAI-Image-2.5. In Text to Image it lands at #7.
On Microsoft Foundry, MAI-Image-2.5-Pro is priced per token: $5 per 1M text input tokens, $8 per 1M image input tokens, and $106 per 1M image output tokens, which works out to roughly $108.5 per 1k 1024x1024 images. That compares to $48 per 1k images for MAI-Image-2.5 and $20 per 1k for MAI-Image-2.5-Flash.
MAI-Image-2.5-Pro is available in preview on Microsoft Foundry across seven global-standard regions, and can be tried out in the MAI Playground.
Congratulations to @MicrosoftAI on the release!
See below for comparisons between MAI-Image-2.5-Pro and other leading models in the Artificial Analysis Image Arena 🧵
Fabian Falck retweeted
Our first reasoning model, MAI-Thinking-1, is built from scratch. Now available in Microsoft Foundry. Kudos to the team! More below.
Fabian Falck retweeted
MAI-Image-2.5-Pro launches today in Foundry for preview. It's our highest-fidelity, professional-grade image model.
It’s for super high quality imagery, detailed editing, precise in-image text rendering. It joins our image family of models so builders can pick the point on the quality-speed-cost curve that fits their job.
More here:
microsoft.ai/news/introducin…
Very excited to share that we are announcing seven (!) new models from Microsoft AI today, including MAI-Thinking-1, which has outstanding performance on reasoning and SWE benchmarks, and MAI-Image-2.5, which outperforms Nano Banana 2 in image editing on LMArena.
Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier.
First is our text foundation model, MAI-Thinking-1, exceptionally strong on reasoning and SWE tasks.
- It’s a 35B active parameter MoE with a 256K context window. Independent human raters on Surge prefer it for overall quality in blind side-by-sides versus Sonnet 4.6, and it’s achieved 97% on AIME 2025, the key measure of its general-purpose reasoning abilities.
- It's at 53% on SWE Bench Pro, placing it right alongside Opus 4.6 on one of the toughest coding benchmarks.
- And since we co-designed our models with our own silicon, MAI-Thinking-1 is optimized on our MAIA 200 chip. Benchmarking head-to-head against the GB200, we see 30% better performance per dollar as well as a 1.4x performance-per-watt gain when running our MAI models on the MAIA 200 end-to-end.
Next is MAI-Image-2.5 and its Flash variant. Two super strong models now at #2 on the leaderboards, surpassing the score of Nano Banana 2 on image editing.
Last for now is MAI-Code-1-Flash, our new inference efficient coding model, especially tuned for VS Code and GitHub Copilot CLI.
- Code-1-Flash achieves 51% on SWE Bench Pro, despite having just 5B parameters, putting it closer to Haiku in size but cheaper in cost.
All of this is the foundation for Microsoft Frontier Tuning. It lets you customize our models to create custom, company-specific agents that only you control. You can make our model, your model. Your data. Your agents. Your moat.
Early adopters are already seeing a difference. When we tuned our models for McKinsey’s tasks, MAI delivered the highest win rate, outperforming GPT-5.5 on quality, while being 10x lower on cost.
Also really excited to be collaborating with the amazing team at Mayo Clinic to jointly train a new frontier AI model for healthcare.
Our announcements today mark another milestone on the road to humanist superintelligence. You can learn more and about our other new models in our latest blog: microsoft.ai/news/building-a…
We're also publishing a tech report discussing how we built MAI-Thinking-1 in great detail: microsoft.ai/wp-content/uplo…
Fabian Falck retweeted
Meet MAI-Image-2-Efficient.
Production-ready quality, 22% faster, and 4x more efficient than MAI-Image-2. Priced almost 41% lower too.
Plus 40% average lower latency than other leading models.
Live now in Microsoft Foundry + MAI Playground. microsoft.ai/news/mai-image-…
ALT Bar chart showing render speeds of MAI-Image-2-Efficient and MAI-Image-2 compared to Gemini 3 Pro Image, Gemini 3.1 Flash Image, Gemini 3.1 Flash Image high reasoning, and GPT Image 1.5 High. MAI-Image-2-Efficient is fastest, followed by MAI-Image-2
Fabian Falck retweeted
Three models. Three top-tier results. All shipped within just a few months by the @MicrosoftAI team.
- MAI-Transcribe-1 dropped today, the most accurate transcription model in the world across 25 languages according to FLEURS WER benchmark.
- MAI-Voice-1 sets a new standard for natural speech.
- MAI-Image-2 lands as a top 3 model family on @arena.
We've been building with them - now you can too. All 3 available now on Microsoft Foundry.
Fabian Falck retweeted
Great to see our new image model from our Superintelligence team rolling out in Copilot and coming soon to Foundry for enterprise customers.
Our new image generator MAI-Image-2 is out! Available now on MAI Playground for everything from lifelike realism to detailed infographics.
Our team has been pushing immensely hard for this release, and we are now among the top models out there: #3 family on @arena.
Check out the details in our blog: microsoft.ai/news/introducin…
It's shipping soon in Copilot and Bing Image Creator, as well as Microsoft Foundry.
Really proud of our progress on models and products - stay tuned for new releases and come join us on our Superintelligence mission!
ALT Screenshot of Arena.ai text-to-image model leaderboard with MAI-Image-2 ranked 5th
ALT Rippled sand dune
ALT Poster for the IAM MAI Cafe with menu items and opening times
ALT Close up of human eye with green iris
Fabian Falck retweeted
Meet MAI‑Image‑2. Built with creatives, for real creative work. Ranked #5 on @arena’s text‑to‑image leaderboard. Available now: msft.it/6014QUCBe
Fabian Falck retweeted
playground.microsoft.ai is now available in the USA and soon all over the world.
Today we unveil our image generation models. Soon everyone will have access to many more models to play with in our playground. Enjoy!
Wanna help build these models? [email protected] - In particular, I'm looking for exceptional data, research and infra engineers.
Fabian Falck retweeted
Super proud of our small image-gen team that in less than 6 months achieved this amazing result.
.... and they're already cooking the next one, but I'm encouraging them all to take a vacation😎
Meet MAI‑Image‑2. Built with creatives, for real creative work. Ranked #5 on @arena’s text‑to‑image leaderboard. Available now: msft.it/6014QUCBe
Fabian Falck retweeted
Coding is only a small fraction of what a CS PhD student actually does; perhaps 10–30% of their time. The real goal of a PhD, and of being a professor, is not to outsource research work but to educate and train the next generation of scientists: people who deeply understand their field, can think critically about it, and ultimately become experts capable of pushing the frontier of knowledge forward.
Coding is probably one of the least interesting part of being a CS PhD. We need human experts even more than before at the age of AI.
In the last few months, I've spoken to many CS professors who asked me if we even need CS PhD students anymore. Now that we have coding agents, can't professors work directly with agents?
My view is that equipping PhD students with coding agents will allow them to do work that is orders of magnitude more impressive than they otherwise could.
And they can be *accountable* for their outcomes in a way agents can't (yet). For example, who checks the agent's outputs are correct? Who is responsible for mistakes or errors?
Authors: Kirill Kalinin, Jannes Gladrow, Jiaqi Chu, James Clegg, Daniel Cletheroe, Doug Kelly. Babak Rahmani, Grace Brennan, Burcu Canakci, Fabian Falck, Michael Hansen, Jim Kleewein, Heiner Kremer, ...