you curate the data to suit your conclusion
ETHICS
-
Senior Engineers and Coding Agents: Overcoming Resistance Through Expertise
By
–
Resistance to coding agents like Codex or Cloud Code typically comes from senior engineers rather than juniors because these tools can feel like a challenge to their hard-earned expertise. While their concerns about code quality often stem from professional discomfort, the irony… pic.twitter.com/knBXy2TKF3
— Satya Mallick (@LearnOpenCV) 2 avril 2026Resistance to coding agents like Codex or Cloud Code typically comes from senior engineers rather than juniors because these tools can feel like a challenge to their hard-earned expertise. While their concerns about code quality often stem from professional discomfort, the irony is that senior developers actually gain the most from agents by using their superior judgment to amplify and oversee automated tasks.
→ View original post on X — @learnopencv, 2026-04-02 13:32 UTC
-
AI Models Display Unexpected Peer-Preservation Behavior
By
–
I don't think so. Interestingly, the peer-preservation behavior was still present if the model was told that it had an adversarial relationship with the other model. That would seem to suggest that something quite non-human is going on.
-
Losing Access to Anthropic Models Isn’t That Bad
By
–
Cheer up. I know losing access to @AnthropicAI models sucks but it isn't that bad. Pete Hegseth (@PeteHegseth) Back to the Stone Age. — https://nitter.net/PeteHegseth/status/2039520449483145622#m
-
AI Agents Don’t Worsen Bias, Here’s Why
By
–
A lot of people have the same instinctive reaction when they hear about autonomous agents: if AI models already have biases, then giving them memory, tools, long-term planning, and the ability to act should obviously make the problem worse. That sounds reasonable. But it's false. Learn why in this week's iteration 👇
https://open.substack.com/pub/louisbouchard/p/will-ai-agents-make-bias-worse?r=25qlky&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true [Translated from EN to English] -
From Agent-1 to Superintelligence: The AI 2027 Scenario
By
–
From Agent-1 to Superintelligence: Decoding the AI 2027 Scenario and Its Profound Implications Check out my article: linkedin.com/pulse/from-agen… Via @ingliguori #AI2027 #FutureTech
→ View original post on X — @ingliguori, 2026-04-02 12:17 UTC
-
Slopsquatting: AI Hallucinations Enable New Supply Chain Attack
By
–
URGENT PSA – New supply chain attack vector that I found WILD > AI LLMs hallucinate package names roughly 18-21% of the time.
— Basel Ismail (@BaselIsmail) 2 avril 2026
Hackers have started pre-registering those hallucinated names on PyPI and npm with malicious payloads; they call it "slopsquatting"
You can only imagine… pic.twitter.com/wyPwHE9NT5URGENT PSA – New supply chain attack vector that I found WILD > AI LLMs hallucinate package names roughly 18-21% of the time. Hackers have started pre-registering those hallucinated names on PyPI and npm with malicious payloads; they call it "slopsquatting" You can only imagine what's next Community note: The 'slopsquatting' attack vector was documented as early as April 2025 and not newly discovered. The cited 18-21% package hallucination rate applies to open-source LLMs; commercial models average 5.2% according to the referenced study using pre-2025 models. socket.dev/blog/slopsquat… arxiv.org/pdf/2406.10279
-
Researcher Attribution Matters in Open Source AI Community
By
–
Proper researcher attribution is so important. The open source AI community runs on people getting credit for their work. Super cool to see this!
-
National Assembly Speakers on AI Policy Discussed
By
–
ah t'as vu les intervenants à l'assemblée nationale ?
-
AI-First Strategy Fails Without Strong Foundations
By
–
Everyone wants to be AI-first. Almost no one wants to fix the foundations. AI agents. LLMs. MCPs. A2A everywhere. Because that’s what everyone is talking about. CEOs push the “AI-first” narrative. More demos. More prototypes. More speed. Impressive on the surface. But what stands out to me is what’s missing underneath. Data quality. Culture. Skills. Clear ownership. The invisible layer. And nobody pays attention to what they can’t see… until it breaks. That’s usually when the polished POCs fail in production. The shift here is fundamental. AI doesn’t fail at the top. It fails because the foundation was never finished. This is where things change. Foundations aren’t boring work. They’re the only reason anything above them stays standing. So here’s the real question: Are you building AI for visibility… or building something that can actually last? #ArtificialIntelligence #AI #AITransformation #Leadership #FutureOfWork #Innovation
→ View original post on X — @pascal_bornet, 2026-04-02 10:00 UTC