Pinned Tweet
Being part of the Science of RL team for Beam has been an absolute privilege. It's been wonderful to learn how the big RL sausage gets made over the last year and a half and witness the dedication and pace of this team. I look forward to building many more models in the future!
Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active.
- Frontier reasoning efficiency
- Advances the Western open frontier on coding & agentic tasks
- Trained end-to-end from scratch
Full weights release this month.
Learn more about Beam8G
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Ben Ellis retweeted
We teamed up with @huggingface to give away $20,000 to anyone who's building with Beam 🤗
Use Beam for any project - make a demo or a dataset, benchmark the model, create an RL environment - and comment your link in the model's repo page by Monday, November 2.
We choose the winners. Winners choose cash or credits. Claim $25 in Hugging Face credits to build with Beam and enter the competition 👇
huggingface.co/reflection/Bea…
Use Beam for any project - make a demo or a dataset, benchmark the model, create an RL environment - and comment your link in the model's repo page by Monday, November 2.
We choose the winners. Winners choose cash or credits. Claim $25 in Hugging Face credits to build with Beam and enter the competition 👇
huggingface.co/reflection/Bea…
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Ben Ellis retweeted
This was the first big run we've done at Reflection. We had a so much fun running a lot of RL on this one! It was very satisfying to see scaling RL in action with no plateau in sight!
Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active.
- Frontier reasoning efficiency
- Advances the Western open frontier on coding & agentic tasks
- Trained end-to-end from scratch
Full weights release this month.
Learn more about Beam8G
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Ben Ellis retweeted
Time to keep scaling
Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active.
- Frontier reasoning efficiency
- Advances the Western open frontier on coding & agentic tasks
- Trained end-to-end from scratch
Full weights release this month.
Learn more about Beam8G
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💯🚀
Special shoutout to the incredibly talented team - @ristovuorio @francismccann14 @benjamin_ellis3 @ThoppilanRomal @brandondamos @RamtinKeramati @jjschwartz12 @the_adam_a. I haven’t seen a set of relentless and creative people like this before.
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Ben Ellis retweeted
Special shoutout to the incredibly talented team - @ristovuorio @francismccann14 @benjamin_ellis3 @ThoppilanRomal @brandondamos @RamtinKeramati @jjschwartz12 @the_adam_a. I haven’t seen a set of relentless and creative people like this before.
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Ben Ellis retweeted
Ben taught me so much about doing proper research in RL and the ways to debug policy gradients. Glad the Science of RL team and @reflection_ai gets to have this expertise for their models!
Being part of the Science of RL team for Beam has been an absolute privilege. It's been wonderful to learn how the big RL sausage gets made over the last year and a half and witness the dedication and pace of this team. I look forward to building many more models in the future!
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Ben Ellis retweeted
Today, we’re introducing Beam, Reflection’s first model.
A year ago, we set out to build a frontier open model before we had much of the team or infrastructure required to do it.
Since then, Reflection has grown 10x. We assembled an extraordinary technical team of researchers and engineers I feel privileged to call my colleagues, alongside a world-class group across recruiting, business, policy, operations, and the rest of the company whose work made all of this possible.
At the same time, we built the science, data, software, and infrastructure behind the model itself. In July, we started pretraining Beam and weeks later, we had a 500B-parameter model at the frontier of Western open intelligence—particularly strong at agentic coding, with remarkable reasoning efficiency.
What makes me proudest, though, is our team. The relentless focus, speed of execution and the willingness to own and solve whatever problem was in front of us. And, most importantly, the commitment of this team to our mission.
Beam is our first milestone toward our mission of building open intelligence and making it accessible to everyone.
We’ll release Beam’s weights, model card, and tech report later this month.
And we’re already training the next, larger model.
Over the past year, we built the team and the engine to propel us to the frontier and that’s what makes me so excited about what comes next.
A year ago, we set out to build a frontier open model before we had much of the team or infrastructure required to do it.
Since then, Reflection has grown 10x. We assembled an extraordinary technical team of researchers and engineers I feel privileged to call my colleagues, alongside a world-class group across recruiting, business, policy, operations, and the rest of the company whose work made all of this possible.
At the same time, we built the science, data, software, and infrastructure behind the model itself. In July, we started pretraining Beam and weeks later, we had a 500B-parameter model at the frontier of Western open intelligence—particularly strong at agentic coding, with remarkable reasoning efficiency.
What makes me proudest, though, is our team. The relentless focus, speed of execution and the willingness to own and solve whatever problem was in front of us. And, most importantly, the commitment of this team to our mission.
Beam is our first milestone toward our mission of building open intelligence and making it accessible to everyone.
We’ll release Beam’s weights, model card, and tech report later this month.
And we’re already training the next, larger model.
Over the past year, we built the team and the engine to propel us to the frontier and that’s what makes me so excited about what comes next.
Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active.
- Frontier reasoning efficiency
- Advances the Western open frontier on coding & agentic tasks
- Trained end-to-end from scratch
Full weights release this month.
Learn more about Beam8G
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Ben Ellis retweeted
We are again recruiting @bold_lab_ai - please share the love 🙏. We are looking for:
1) Postdocs (my.corehr.com/pls/uoxrecruit…) -- deadline 9th of Oct at noon
2) research assistants (my.corehr.com/pls/uoxrecruit…) -- deadline 9th of Oct at noon
3) Strategic Partnership Project Manager (my.corehr.com/pls/uoxrecruit…) -- deadline 14th of Oct at noon
1) Postdocs (my.corehr.com/pls/uoxrecruit…) -- deadline 9th of Oct at noon
2) research assistants (my.corehr.com/pls/uoxrecruit…) -- deadline 9th of Oct at noon
3) Strategic Partnership Project Manager (my.corehr.com/pls/uoxrecruit…) -- deadline 14th of Oct at noon
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Ben Ellis retweeted
The UK’s most powerful government-built AI supercomputer, Isambard-AI, cost £225m
The Botley Road bridge cost roughly the same
Apparently our frontier AI capacity and one bridge are comparable national investments
The Botley Road bridge cost roughly the same
Apparently our frontier AI capacity and one bridge are comparable national investments
Cars and buses go from Oxford Station down Botley Road for the first time in three years!
The project took longer than the construction of The Titanic and saw costs balloon to £237m.
Looks good though.
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BOLD is an exciting initiative with a lot of compute for academia. If you want to explore new ideas, this is a great place to be! My time at its previous incarnation (FLAIR) taught me almost everything I know about ML.
TL;DR: This is one of the most important and exciting opportunities in AI on the planet - please read on.
The British Open-ended Learning & Discovery Lab is creating the perfect place for paradigm breaking AI research in the name of open-source and open-science. We have agency, we fdented amounts of compute*, but WE NEED YOU!
..and we have created the dream job for you: The BOLD Fellow. This job combines a fast-moving, high agency, collaborative environment with full academic freedom and a salary that pays the bills.
Apply by noon UK time on the 15th of September for this once in a lifetime opportunity to shape the history of our field and of our planet:
my.corehr.com/pls/uoxrecruit…
*by academic standards
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Ben Ellis retweeted
TL;DR: This is one of the most important and exciting opportunities in AI on the planet - please read on.
The British Open-ended Learning & Discovery Lab is creating the perfect place for paradigm breaking AI research in the name of open-source and open-science. We have agency, we fdented amounts of compute*, but WE NEED YOU!
..and we have created the dream job for you: The BOLD Fellow. This job combines a fast-moving, high agency, collaborative environment with full academic freedom and a salary that pays the bills.
Apply by noon UK time on the 15th of September for this once in a lifetime opportunity to shape the history of our field and of our planet:
my.corehr.com/pls/uoxrecruit…
*by academic standards
The British Open-ended Learning & Discovery Lab is creating the perfect place for paradigm breaking AI research in the name of open-source and open-science. We have agency, we fdented amounts of compute*, but WE NEED YOU!
..and we have created the dream job for you: The BOLD Fellow. This job combines a fast-moving, high agency, collaborative environment with full academic freedom and a salary that pays the bills.
Apply by noon UK time on the 15th of September for this once in a lifetime opportunity to shape the history of our field and of our planet:
my.corehr.com/pls/uoxrecruit…
*by academic standards
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Ben Ellis retweeted
What UK AI startups need: @KanishkaNarayan
In California, one can start a company the day after leaving Google. My colleagues Jeff Dean, Oriol Vinyals et al made this very clear recently with their impressive speed.
In the UK, the same American companies impose 1 year garden leaves on senior AI researchers and 6 months on junior researchers. @GoogleDeepMind for example forced people to sign these contracts at the time of promotion, not the time of hiring.
What this means is that researchers cannot start new companies for up to 1 year, cannot easily hire, and in short: they cannot compete.
American VCs cannot understand why we move so slow.
It is time for UK Gov to do the right thing: Make garden leaves optional for employees.
If you’re an AI entrepreneur or VC in the UK or Europe, I would appreciate your comments here. You’ve all confided in me. It is time you let government know the urgency of this — everyone should speak up.
In California, one can start a company the day after leaving Google. My colleagues Jeff Dean, Oriol Vinyals et al made this very clear recently with their impressive speed.
In the UK, the same American companies impose 1 year garden leaves on senior AI researchers and 6 months on junior researchers. @GoogleDeepMind for example forced people to sign these contracts at the time of promotion, not the time of hiring.
What this means is that researchers cannot start new companies for up to 1 year, cannot easily hire, and in short: they cannot compete.
American VCs cannot understand why we move so slow.
It is time for UK Gov to do the right thing: Make garden leaves optional for employees.
If you’re an AI entrepreneur or VC in the UK or Europe, I would appreciate your comments here. You’ve all confided in me. It is time you let government know the urgency of this — everyone should speak up.
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Ben Ellis retweeted
Hello world :)
We are BOLD — the British Open-ended Learning and Discovery Lab!
BOLD is a new academic research lab fully focussed on paradigm breaking discoveries in fundamental AI. We work towards more efficient & open AI that is built around human needs and capabilities.
To ghs, we pioneer new modes of collaboration in academia that are more focussed, resourced, agile, and collaborative. Rather than fragmenting resources, today we are sunsetting 5 of the UKs leading AI labs to join forces under our joined scientific vision.
Our vision is centered around three pillars:
⚡ Beyond backpropagation – questioning the foundations of the field.
🤝 Human-centric learning & discovery – treating humans as core to our algorithms
🤖 Embodied learning – fast learning and adapting methods that deal with the messy real world
BOLD is backed by @UKRI_News and @EPSRC with £30M – and this is just the beginning. We are urgently looking for partners and sponsors to 10x this.
👉 ox.ac.uk/news/2026-06-2…
👉 bold-lab.ai
@j_foerst, @CULLYAntoine, @tonizza82, @shimon8282, @tonizza82, Ani Calinescu & @_rockt
We are BOLD — the British Open-ended Learning and Discovery Lab!
BOLD is a new academic research lab fully focussed on paradigm breaking discoveries in fundamental AI. We work towards more efficient & open AI that is built around human needs and capabilities.
To ghs, we pioneer new modes of collaboration in academia that are more focussed, resourced, agile, and collaborative. Rather than fragmenting resources, today we are sunsetting 5 of the UKs leading AI labs to join forces under our joined scientific vision.
Our vision is centered around three pillars:
⚡ Beyond backpropagation – questioning the foundations of the field.
🤝 Human-centric learning & discovery – treating humans as core to our algorithms
🤖 Embodied learning – fast learning and adapting methods that deal with the messy real world
BOLD is backed by @UKRI_News and @EPSRC with £30M – and this is just the beginning. We are urgently looking for partners and sponsors to 10x this.
👉 ox.ac.uk/news/2026-06-2…
👉 bold-lab.ai
@j_foerst, @CULLYAntoine, @tonizza82, @shimon8282, @tonizza82, Ani Calinescu & @_rockt
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Ben Ellis retweeted
After interviewing for Research Scientist roles at DeepMind, Isomorphic, Meta, Cohere and more, I wrote up everything I learned. Technical prep, logistics, negotiation, and emotional breakdowns. Check out my guide: silviasapora.github.io/blog/ml-interv…
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Ben Ellis retweeted
Hindsight Experience Replay has become the ubiquitous method for goal-conditioned reinforcement learning, but leaves open the question of which goal to relabel with.
In this work, accepted at ICML, we propose instead simply Learning Everything All at Once (LEO).
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In this work, accepted at ICML, we propose instead simply Learning Everything All at Once (LEO).
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