Around 15 years ago, Kaheer Suleman and I started Maluuba with the vision of building Universal Turing Machines. Back then, we were one of the pioneer research labs building foundational modules of deep learning and Reinforcement learning with Turing award winners @Yoshua_Bengio and @RichardSSutton. There was no AI hype then, as there is now. Those were the good old days of doing pure scientific research unlike the n+1 research that we see today. Maluuba was later acquired by Microsoft and became @MSFTResearch Canada.
Grounded in that same mission, we're finally ready to introduce @skyfallai to the world after a lot of experimentation in stealth over the last year. We're a frontier neo lab building the first Autonomous Enterprise by moving beyond the current LLM paradigm.
For the last 5 years, the foundational model market has relied on a single paradigm: scaling laws for LLMs - more data, more compute, bigger models. However, the real world is messy and much more complicated. In order to achieve our long term vision, the next generation of AI models requires a different approach. Skyfall is solving the hardest open problems in frontier AI: long-horizon planning, data inefficiency, and brittle performance in dynamic real-world environments.
To achieve the team's vision of a completely autonomous enterprise, the team is developing a next-generation frontier model (Enterprise World Models) using Continual Learning and World Modeling. Enterprise World Models can simulate the multi-layered consequences of strategic business actions. Our approach unlocks a new category in the foundation model market. To prove it, we're introducing Morpheus, a Continual Reinforcement Learning platform for AI researchers.
I'm building this company with the people I trust the most: my longtime friend Kaheer Suleman (prev. Co-Founder of Maluuba) and my brother @omgiamgod (prev. YC founder). Sumit and Kaheer are the first principles thinkers I can trust to go to the end of the world with to achieve the mission impossible together. Together with a stellar team of 25 researchers and engineers, we're pushing a new frontier in AI forward.
We unpacked our long term vision in today’s Forbes feature 🔗- read it to see what we’re building toward. Thank you so much Victor Dey for the interview.
To achieve our goal of enterprise world models, we are soliciting bids to acquire small SaaS startups (up to $1M) and fully automate them. If you’re interested, submit your business here: https://t.co/w8ayopZFLH
Finally, thank you to our investors and advisors for believing in our vision since day one: @Fidelity , @sk121 (@touringcapital), @karam_n and @chrisarsenault (@inovia), @morgan_blumberg (@M13Company ), @stephpalmeri (@NextViewVC ), and @michaellitt and @mmccauley (@GarageCapital ), @jennydhe, @fchollet@NaveenGRao and so many others for supporting us in this journey.
The era of new model launches as big milestones will eventually come to an end -- at some point they will simply be continuously updated, with no widely publicized version number. Probably less than 2 years away
We’re at a pivotal moment in the AI revolution right now but Canada doesn't get as much credit.
Canada's AI talent pool is exceptional and yet is still underrated since SF takes all the credit. Canada has produced pioneers and leaders in AI such as nobel prize winners @GeoffreyHinton, Turing award winners @Yoshua_Bengio and @RichardSSutton, OpenAI founders @ilyasut and @karpathy, amongst countless others.
At https://t.co/E0sZ94eJHQ, we are doing fundamental AI research in the post-LLM era and we are building our research team out of Toronto. Given the huge density of high profile AI talent at @UofT , @UWaterloo , @Mila_Quebec and @amiithinks, we believe that this is one of the best places in the world to do AI research.
Thanks to @BetaKit for sharing our story about building our AI research lab from Canada. We are very grateful about the fact that 15 years ago we also hired the best and brightest minds in Canada at Maluuba during the early stages of the deep learning revolution. We will keep investing in Canada for the years to come.
.@travisk describes his management style as “problem solver in chief."
- He spends his time on the biggest problems no one else is solving
- He expects every direct report to bring the same mentality to their org
“There’s only 24 hours in a day. I can only solve so many myself. They have to take that for their world and do the same thing.”
Around 15 years ago, Kaheer Suleman and I started Maluuba with the vision of building Universal Turing Machines. Back then, we were one of the pioneer research labs building foundational modules of deep learning and Reinforcement learning with Turing award winners @Yoshua_Bengio and @RichardSSutton. There was no AI hype then, as there is now. Those were the good old days of doing pure scientific research unlike the n+1 research that we see today. Maluuba was later acquired by Microsoft and became @MSFTResearch Canada.
Grounded in that same mission, we're finally ready to introduce @skyfallai to the world after a lot of experimentation in stealth over the last year. We're a frontier neo lab building the first Autonomous Enterprise by moving beyond the current LLM paradigm.
For the last 5 years, the foundational model market has relied on a single paradigm: scaling laws for LLMs - more data, more compute, bigger models. However, the real world is messy and much more complicated. In order to achieve our long term vision, the next generation of AI models requires a different approach. Skyfall is solving the hardest open problems in frontier AI: long-horizon planning, data inefficiency, and brittle performance in dynamic real-world environments.
To achieve the team's vision of a completely autonomous enterprise, the team is developing a next-generation frontier model (Enterprise World Models) using Continual Learning and World Modeling. Enterprise World Models can simulate the multi-layered consequences of strategic business actions. Our approach unlocks a new category in the foundation model market. To prove it, we're introducing Morpheus, a Continual Reinforcement Learning platform for AI researchers.
I'm building this company with the people I trust the most: my longtime friend Kaheer Suleman (prev. Co-Founder of Maluuba) and my brother @omgiamgod (prev. YC founder). Sumit and Kaheer are the first principles thinkers I can trust to go to the end of the world with to achieve the mission impossible together. Together with a stellar team of 25 researchers and engineers, we're pushing a new frontier in AI forward.
We unpacked our long term vision in today’s Forbes feature 🔗- read it to see what we’re building toward. Thank you so much Victor Dey for the interview.
To achieve our goal of enterprise world models, we are soliciting bids to acquire small SaaS startups (up to $1M) and fully automate them. If you’re interested, submit your business here: https://t.co/w8ayopZFLH
Finally, thank you to our investors and advisors for believing in our vision since day one: @Fidelity , @sk121 (@touringcapital), @karam_n and @chrisarsenault (@inovia), @morgan_blumberg (@M13Company ), @stephpalmeri (@NextViewVC ), and @michaellitt and @mmccauley (@GarageCapital ), @jennydhe, @fchollet@NaveenGRao and so many others for supporting us in this journey.
Yesterday, we came out of stealth at @skyfallAI in Forbes and today we're excited to announce that Skyfall AI is featured in the @WSJ's newsletter.
We believe in a utopian world that will be achieved over the next decade, where humans will work in their own creative interests in space exploration, sports, arts or philosophy while machines will do all the mundane operational tasks. We want to free humanity from all the monotonous boring operational tasks that they spend their daily lives doing.
The only way to achieve this vision is via creating autonomous enterprises, i.e., companies that can run by themselves with minimal human intervention. After 15 years of building in the AI space, one thing is certain. LLMs are static systems that fail at
- Long horizon planning tasks
- High consequential decision-making
- Sample efficiency
- Dynamic environment adaptation
These skills are required by a business to survive and grow. Unfortunately, LLMs are not designed for the real world constraints of running an organization.
Our solution is Enterprise World Models grounded in Continual Learning and World Modeling. We're taking a fundamentally different approach because we have always believed in 0 to 1 research, and not incremental n+1 RL fine tuning.
We are acquiring SaaS businesses to prove our thesis for creating AI systems for the post scarcity world. This is a call to all SaaS founders to submit your company if you’re interested (🔗 in comments)
Thank you Sarah @sarahklearman for covering our story on @WSJ
There are plenty of AI labs improving today's AI.
Very few are trying to build what comes next.
That's what makes @skyfallai interesting.
Led by Sam Pasupalak @spisallyouneed, who built and sold Maluuba to Microsoft for $160M, the team is focused on Continual Learning and World Models instead of simply scaling LLMs.
At Maluuba, Sam worked alongside Turing Award winners Yoshua Bengio and Richard Sutton on foundational deep learning research.
Now he's tackling some of AI's hardest problems: long-horizon planning, data inefficiency, and making AI reliable in dynamic real-world environments.
Skyfall is positioning itself as a neo lab building toward the first Autonomous Enterprise.
It's a different bet from most of the industry, and one worth watching.
15 yrs ago @spisallyouneed and I were building our companies side by side @UWVelocity.
His intensity + vision was inspiring and hard to miss.
Then it was an AI lab MSFT bought for $160M.
Now: AI that runs a company autonomously.
Proud to back @skyfallai via @GarageCapital.