Edward Grefenstette
@egrefen · London, United Kingdom · joined 29 Apr 2007
FR/US/GB AI/ML Person, Director of Research at @GoogleDeepMind, Honorary Professor at @BOLD_Lab_AI, @ELLISforEurope Fellow. All posts are personal.
46 475Followers
926Following
16 152Posts total
290.2KViews on collected posts
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Disappointed to hear the @TfL announcement system in King's Cross blast an @audible_com announcement formatted as a normal announcement. Misleading, tasteless, and unwelcome.
3.1K views · 18 likes
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"SPCX to the moon 🚀🚀🚀" bros have really gone silent, haven't they 😅
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So... solving reward hacking necessary for RSI, you say? 🤔😉
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It's recursive self-improvement if it works, reward hacking if it doesn't.
18.8K views · 208 likes
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Amazing launch, @redpony and team! Great to see Google ship technology in this space 🥰
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@egrefen Because I consider you a researcher and scientist this concerns and troubles me deeply: "...or ever?..."
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As always, I end this thread with a reference to last year's. Happy end of 2025, everyone, and best wishes for the new year! 🥳🎉 [12/12]
https://t.co/vjYiV0Cx1b
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On the personal front, I've been focussing on trying to be a good dad, become a better golfer, and be more organized. I did two years of BuJo for task management and am think about doing something more integrated into my Obsidian workflow in the new year.… [11/12]
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We also published https://t.co/QNs4JcCnME about a year or so after the work was done. I can't comment on if, where, or how this might be used internally. [10/12]
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Along the way we published a few technical reports such https://t.co/BTs8zoiL2Y or https://t.co/G8oalLHWrb, which can be seen as hints of the broader directions we are looking at. [9/12]
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We've also made some progress in terms the actual learning process itself, allowing open-ended agents, at the instance level, to learn and adapt with human-like data efficiency. This potentially points at a broader way of improving agents at scale, which we are working on. [7/12]
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On the more theoretical front, we've been interested in what it actually *means* to have complementary/cooperative agents, rather replacements of our own agency, and also how agents could self-motivate. I want to stress that these are both unsolved, open questions. [8/12]
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I can't say much more, but I did give some general high level directions of interest at keynote I gave the SEA workshop at NeurIPS: https://t.co/I5n9bVQhPl
Perhaps the video will be put online in the next month or so... [5/12]
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Broadly, we've been making good progress with regard to how open-ended agents can learn "in the wild", with less human intervention in their learning process, while still ensuring they remain aligned with human behaviors and interests. [6/12]
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With my broad circle of collaborators, we've investigated some interesting questions at the frontier of what's possible with contemporary AI, to (potentially) power the models of tomorrow and (maybe) some of today. [4/12]
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At @GoogleDeepMind I continue to collaborate with a broad set of wonderful people across Frontier AI and Gemini teams. In particular with @SianGooding, Lucia Lopez, João Araújo, Yusra Ibrahim, @MartinKlissarov, @jingling_li, @HolarisSun, and many others I see near daily. [3/12]
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🧵 Time for a short end-of-2025 wrap up 🧵
Genuinely aiming for this to be a short one for two reasons:
1. I'm doing it at the last moment 😅
2. Most of what I was involved in is not stuff that can be shared publicly (yet… or ever?). Or maybe I was just lazy...
Let's go [1/12]
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On the UCL front, @akbirkhan and @_robertkirk, who had started at Anthropic and AISI, formally finished their PhDs early in the year, leaving me with two PhD students. @LauraRuis completed hers more recently and is now doing a postdoc at MIT. Down to one… [2/12]
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🧵 As 2024 wraps up, please pardon my usual self-indulgence in tweeting about the year gone by. 🧵
This will be a reasonably short one... OR WILL IT? [1/17]
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Im Vergleich zu Konten gleicher Größe
5 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.
Medianaufrufe3 661dieses Konto924Median für 10K–100K
Reichweite, %7.88%dieses Konto3.62%Median für 10K–100K
Interaktion, %0.56%dieses Konto1.52%Median für 10K–100K
| Kennzahl | Dieses Konto | Median für 10K–100K | Verhältnis |
|---|---|---|---|
| Medianaufrufe pro Beitrag | 3 661 | 924 | 3.96× |
| Reichweite (Aufrufe ÷ Follower) | 7.88% | 3.62% | 2.18× |
| Interaktionsrate | 0.56% | 1.52% | 0.37× |
Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
12.4K31 Dec
5.4K
5K
75.1K
5.1K
3.9K
4.3K
5.4K
2402 Jan
3.6K12 Aug
18.8K18 Aug
5.1K19 Aug
3.7K21 Aug
3.1K3 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.75%31 Dec
1.23%
1.27%
0.26%
1.07%
1.22%
1.08%
0.77%
0.42%2 Jan
0.56%12 Aug
1.17%18 Aug
0.41%19 Aug
0.27%21 Aug
0.58%3 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes70.0%1 167 in total
Reposts4.3%71 in total
Replies2.9%48 in total
Quotes1.5%25 in total
Bookmarks21.4%357 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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