Human And Machine: The Future Of #AI Lies In Collaboration, Not Replacement
by Sylvio Lindenberg @Forbes Learn more: https://
bit.ly/3PBZYB1 #ArtificialIntelligence #MachineLearning #ML #DL
RESEARCH
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Human And Machine: AI’s Future In Collaboration Not Replacement
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OpenAI and Google Face Book Memorization Scandal
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🚨 BREAKING: OpenAI and Google are about to have a massive legal problem. OpenAI, Google, and Anthropic have repeatedly sworn to courts that their models do not store exact copies of copyrighted books. They claim their "safety training" prevents regurgitation. Researchers just dropped a paper called "Alignment Whack-a-Mole" that proves otherwise. They didn't use complex jailbreaks or malicious prompts. They just took GPT-4o, Gemini, and DeepSeek, and fine-tuned them on a normal, benign task: expanding plot summaries into full text. The safety guardrails instantly collapsed. Without ever seeing the actual book text in the prompt, the models started spitting out exact, verbatim copies of copyrighted books. Up to 90% of entire novels, word-for-word. Continuous passages exceeding 460 words at a time. But here is the part that changes everything. They fine-tuned a model exclusively on Haruki Murakami novels. It didn't just learn Murakami. It unlocked the verbatim text of over 30 completely unrelated authors across different genres. The AI wasn't learning the text during fine-tuning. The text was already permanently trapped inside its weights from pre-training. The fine-tuning just turned off the filter. It gets worse. They tested models from three completely different tech giants. All three had memorized the exact same books, in the exact same spots. A 90% overlap. It's a fundamental, industry-wide vulnerability. For years, AI companies have argued in court that their models are just "learning patterns," not storing raw data. This paper provides the smoking gun. [Translated from EN to English]
→ View original post on X — @flashtweet, 2026-04-01 10:36 UTC
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AI in RAN: Three Distinct Applications and Performance Gains
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First, let’s clarify something most people miss: There isn’t just “AI in telecom.” There’s: → AI in RAN
→ AI for RAN
→ AI on top of RAN AI in RAN is where things get tangible. We’re talking: → 20% improvement in uplink spectral efficiency
→ 14% energy savings with -
AI Winners: Data Quality Over Engineering Talent
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But the real shift isn’t just better models. It’s better data. Joe Constantine made a point I fully agree with: The winners in AI won’t be the companies with the best AI engineers. They’ll be the ones with: → Real-time data
→ Trusted data
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Autonomous AI self-improvement capabilities
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Not true the bleeding edge AI geniuses tell me. One told me their team went totally autonomous and it started improving itself faster than when they were involved.
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Sustained Reasoning as the Key AI Benchmark Test
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indeed. Sustained reasoning will be the real benchmark test
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Secretary Krishnan Outlines India’s AI Priorities for 2026-2028
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Shri S. Krishnan, Secretary, @GoI_MeitY , outlines the key priorities for the next 2–3 years, with a strong focus on making AI resources more accessible, inclusive and scalable across sectors.
— IndiaAI (@OfficialINDIAai) 1 avril 2026
A forward-looking vision to ensure that AI innovation reaches every stakeholder, from… https://t.co/JKiyu4ic45Shri S. Krishnan, Secretary, @GoI_MeitY , outlines the key priorities for the next 2–3 years, with a strong focus on making AI resources more accessible, inclusive and scalable across sectors. A forward-looking vision to ensure that AI innovation reaches every stakeholder, from startups and researchers to government and industry. ▶️ Watch the full conversation: piped.video/NgfnFCaGeqI?si=6NHl… #IndiaAI #DigitalIndia #AIForAll #AIInfrastructure #Innovation NIC (@NICMeity) Shri S. Krishnan, Secretary, @GoI_MeitY, outlines key priorities for the next 2 to 3 years, with a strong emphasis on making AI resources accessible. Watch full conversation▶️ piped.video/NgfnFCaGeqI?si=6NHl… #NICMeitY #DigitalIndia #IndiaAIImpactSummit @SecretaryMEITY @OfficialINDIAai — https://nitter.net/NICMeity/status/2039251564670632123#m
→ View original post on X — @officialindiaai, 2026-04-01 08:26 UTC
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Developing Transparent and Explainable AI Systems
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Developing Transparent and Explainable #AI Systems
by @antgrasso #ArtificialIntelligence #MachineLearning #ML #DL -
AI Fundraising Milestone for Cancer Research Initiative
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Wow ma cagnotte pour #Medicbrain vient d'atteindre 1 million d'euros ! Je ne sais pas quoi dire, pour vous remercier. Vous êtes formidables. Merci pour vos partages et vos engagements et vos dons. On va pouvoir trouver des solutions contre les cancers avec l'IA. Je vais
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OpenAI’s Internal Model Solves Three Classic Erdos Problems
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Three new Erdos problems were solved „by an internal model at OpenAI“.