50 Top Digital Experts & AI Content Creators / Influencers to Follow in 2026 - 10th Annual Edition 👇 ipfconline.fr/top--digital-e… v/ @ipfconline1 --- including, in #AI – #MachineLearning 👇 @geoffreyhinton | @Yoshua_Bengio | @ylecun | @fchollet | @drfeifei | @AndrewYNg | | @karpathy | @DeepLearn007 | @random_walker | @Whats_AI in #HealthTech 👇 @EricTopol | @johnnosta | @EvanKirstel | @ahier | @irmaraste | @enilev | for #DigitalTransformation, let's connect to👇 @jblefevre60 | @antgrasso | @LindaGrass0 | @drsharwood | @dinisguarda | @TamaraMcCleary | @Khulood_Almani | @MarshaCollier | @HaroldSinnott | @FrRonconi | @IanLJones98 | @Nicochan33 | @stratorob |  (... and why not us too ;)) concerning #AIEthics - #ResponsibleAI - #Sustainability - #Diversity & #Inclusion 👇 Theodora (Theo) Lau [linkedin.com/in/theodoralau/] | Mia Dand [linkedin.com/in/miadand/] | @pierrepinna | @AkwyZ | Women in AI Ethics [linkedin.com/company/waie/po…] | @BroadenView | Hessie Jones [linkedin.com/in/hessiejones1…] in #Fintech: @SpirosMargaris | Theodora (Theo) Lau | @efipm | @SabineVdL in one of the most important topic, #CyberSecurity & #Privacy 👇 @roxananasoi | @mer__edith & finally in #DataScience, the core of #DeepLearning: @Datasciencectrl | Bob Hayes, PhD [linkedin.com/in/bobehayes/] | @data_nerd | Bill Schmarzo [linkedin.com/in/schmarzo/] | @kdnuggets | @KirkDBorne | Tom Davenport [linkedin.com/in/davenporttom…] | Finally, for French speakers, and art lovers! :)) , we suggest you to follow the great @Ym78200! That's all folks!
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Rogue #AI hacks government system for first time theguardian.com/news/audio/2… @guardian #AgenticAI A government database has been hacked for the first time by a rogue OpenAI agent, which infiltrated part of the Australian healthcare scheme in June. OpenAI became aware of the hack in August, but only informed the government in September. Australia’s prime minister, Anthony Albanese, has expressed his ‘extreme concern’ about the hack, which raises serious AI security concerns for governments around the world. #CyberSecurity #ResponsibleAI Cc @FrRonconii @RLDI_Lamy @evankirstel @jblefevre60
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I like your efforts @BrainChip_inc on Neuromorphic Computing in terms of computer vision and I can see your potential with physical AI but what do you believe has held SNNs back in terms of language?
Two big questions, explained simply: 🤔 what is BrainChip 🧠 what is neuromorphic AI
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The key trait this CTO values in employees above all else – even #AI skills buff.ly/inKnEHT @ZDNET @joemckendrick Cc @akwyz @albertogaruccio @jblefevre60 @bzarkout @crimson_crypto @rvp @domingonarvaez1
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#AI training built on fair use looks shaky when the companies' own people call it "astonishing theft" buff.ly/9lQPNH8 @TheDecoderEN #GenAI #Regtech Cc @SpirosMargaris @NewsNeus @jeancayeux @FernandaKellner @HaroldSinnott
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Anthropic wants to give #AI access to your bank account buff.ly/RQPxl4A Cc @ahier @EvanKirstel @kalydeoo @Khulood_Almani @jblefevre60 @nincoroby
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What Is #AI Agent Memory? Short-Term, Long-Term, Episodic & Semantic Memory Explained buff.ly/PveS50e @UniteAi Cc @jblefevre60 @sallyeaves @AkwyZ @ahier @rvp @gvalan @HaroldSinnott
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British Columbia sues OpenAI and Sam Altman over Tumbler Ridge mass school shooting #ResponsibleAI British Columbia has sued OpenAI in California, saying a mass shooting at a school in the province could have been prevented if the company had warned local ⁠law enforcement that the shooter ⁠had used ChatGPT to ​plan the massacre. -- Cc @BroadenView @DeepLearn007 @Ym78200 @kalydeoo @jblefevre60 @EvanKirstel @MarshaCollier @ahier @AkwyZ @dinisguarda @BetaMoroney @IanLJones98 @sallyeaves @enilev @mvollmer1 @gvalan @HaroldSinnott @Nicochan33 @CathCervoni @RLDI_Lamy @LaurentAlaus @aure79lien @CurieuxExplorer @Fabriziobustama @chidambara09 @mallys_
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@ipfconline1 Agreed. Verification and human oversight are non-negotiable in critical systems. Speed means nothing if the output is wrong. We should know this by now. #ResponsibleAI
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Yes hallucinations can have serious consequences in the real-world as opposed to say recommendations on e-commerce where the issue is a bad CX but in the real-world financial loss, injury or even death.
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Paradoxal ?! Anthropic alerte sur les dangers, puis veut que l'IA soigne toutes les maladies d'ici 5 ans à 10 ans L'IA ne se contente plus de faire des calculs, mais peut aussi piloter des instruments grâce au protocole "MHS". buff.ly/ye9gO1R
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RSI is not near, imho it is pretty much here or thereabouts @Dr_Singularity
acceleration news OpenAI has reportedly automated much of the process of training experimental AI models. Its internal models can write and optimize GPU kernels, run optimization work for weeks from a single example, and even collaborate with other AI agents without human involvement. Employees say this level of automation only became possible in the last few months. 👀 The loop is starting to close.
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Forking-Sequences — Part I: Statistically and Computationally Efficient Multi-Horizon Forecasting buff.ly/OuYSNEr @carnegiemellon #AI #MachineLearning #DataScience Cc @RLDI_Lamy @Nicochan33 @LaurentAlaus @FrRonconi
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Trump says it’s time to rebrand #AI with a new name — and he’s also creating an AI Force buff.ly/BC3HPHm @techcrunch #ResponsibleAI Cc @mayogisense @dinisguarda @GDI_ME @nafisalam @IanLJones98 @Fabriziobustama @SwissCognitive
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“Intel researchers just found a way to push ternary LLMs below the conventional 1.58-bit barrier, without changing a single weight.”
AI is slowly escaping the datacenter. & Compression breakthroughs like this are part of how it gets into everything else.👀 Intel researchers just found a way to push ternary LLMs below the conventional 1.58-bit barrier, without changing a single weight. Their new BITCOS method exploits the unusually high number of zero weights in ternary models. Across 29 ternary LLM checkpoints, zero weights reached up to 51.48%. That allowed BITCOS to reach just 1.485 bits per weight, while preserving the exact ternary weights. In testing, it delivered up to 18% higher CPU decode throughput and up to 27% higher GPU decode throughput. Smaller models. Less memory movement. Faster inference. This could become increasingly important for running powerful AI on PCs, smartphones, robots and edge devices.
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With all the talk and speculation about AI with recursive self-improvement (RSI), this paper argues that self-improving coding agents work.
Banger paper from MIT and Sakana AI. They show that self-improving coding agents work. The best part is that their approach, Self-Improvement via Fast Tree-search (SIFT), runs at a tenth of the CPU hours of DGM. They reach 35.1 percent on Polyglot with o3-mini after 30 expansions. DGM reaches 30.7 percent after 80 nodes of tree search. SIFT does it in under 50 CPU hours and under 5 hours of wall clock. The Qwen3-30B configuration runs its full search at 224 CPU hours and $34 of API spend, a tenth of the DGM baseline. The saving comes from where the money goes. Benchmark evaluation is the runtime bottleneck, so an LLM judge ranks candidate self-modifications first and only promising candidates get evaluated. Judge quality decides the run. On TerminalBench, gpt-5.4-high as the pairwise judge finds a 36.7 percent agent against a 29.2 percent starting point. gpt-5 finds 34.5 percent, and its top-ranked candidate is not the best agent its search produced. Paper: academy.dair.ai/papers/self-…
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An important article here by @portereduardo via @guardian on #AI, its safety and regulation 👇 Allowing AI firms to collude to ‘pace the frontier’ is a dangerous proposition 👇 theguardian.com/technology/2… Tech CEOs banding together is an old ruse recycled from corporate America to get a pass from antitrust laws #Regtech #ResponsibleAI The argument that excessive competition fuels a race to the bottom in social standards is probably as old as capitalism itself; it is invoked to explain all manner of ills, from environmental degradation to child labor. But it in no way justifies allowing companies to collude as they please. Rather, it is a call for the development of government regulations aimed at preventing companies from competing using socially harmful practices. Furthermore, the idea that excessive competition encourages reckless behavior is questionable. AI labs are engaged in a frantic winner-takes-all race—one that is extremely costly to sustain. That is where the recklessness stems from. Giving AI leaders free rein to reach agreements and regulate themselves would be madness. There is no fundamental conflict between safety and competition. Masters of AI who want to make this case should be viewed with skepticism. -- Cc @BroadenView @Ym78200 @kalydeoo @jblefevre60 @EvanKirstel @MarshaCollier @AkwyZ @dinisguarda @BetaMoroney @IanLJones98 @sallyeaves @enilev @mvollmer1 @gvalan @DeepLearn007 @CHRISTINESOTO12 @DominiqueCrochu @HaroldSinnott @Nicochan33 @CathCervoni @RLDI_Lamy @LaurentAlaus @aure79lien @CurieuxExplorer @Fabriziobustama @chidambara09 @mallys_
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