From data to impact: IDC shows how AI fuels #businesstransformation. Text, audio, video, and code converge in #AI models, driving industry advancements and productivity
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AI Drives Business Transformation: Data to Real-World Impact
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AI Giants Face Legal Challenges Amid Generative Video Breakthroughs
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Les sources de l'édition du jour du #FlashTweet https://
usine-digitale.fr/article/nouvel
le-plainte-d-auteurs-contre-openai-et-microsoft-pour-violation-de-la-propriete-intellectuelle.N2197838?utm_source=newsletter&utm_medium=email&utm_campaign=info_ud-quotidienne&email=96991387&idbdd=56561
… @LUsineDigitale https://
engadget.com/the-ai-startup
-behind-stable-diffusion-is-now-testing-generative-video-105519658.html?src=rss&_guc_consent_skip=1700676358
… @Engadget https://
maddyness.com/2023/11/22/com
ment-callyope-veut-reinventer-le-suivi-des-troubles-mentaux/
… @byMaddyness https://
usine-digitale.fr/article/grace-
a-l-ia-generative-nvidia-triple-son-chiffre-d-affaires.N2197513
… @LUsineDigitale https://
cnbc.com/2023/11/22/ai-
is-giving-big-tech-inordinate-power-tech-execs-say.html
… @CNBC -
Tom Nides Joins AI21’s Board of Advisors
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Welcome Tom Nides, former US Ambassador to Israel, to AI21's Board of Advisors! We look forward to working together and learning from his unique perspective of the financial market. Glad to have you on board, Tom!
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OpenAI Microsoft lawsuit and Nvidia AI breakthroughs
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#FlashTweet, le petit journal des grandes innovations
Édition SPÉCIALE IA du 23 novembre 2023 @EmmanuelleL9 vous briefe sur les avancées de l’IA … le jeudi aussi Première plainte contre OpenAI et Microsoft, les bénéfices fous de Nvidia, la vidéo générée par IA de -
Genome Data Constraints and Human Cognitive Capability Development
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1. The amount of data in the human genome is small: 800MB. The difference between chimp and human genomes is about 8MB. That's just not enough "instructions" to explain the difference in capability. 2. The total amount of visual data seen by a 2 year-old is pretty small:
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LLM Evaluation Methods: Comparing Text Robustness Techniques
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any reasonably competent LLM should be sufficient to evaluate, as LLMs are a lot more robust to comparing two texts (than to evaluate an answer in isolation). I'd say one can even just do cosine distance on sentence embeddings if we want to avoid the LLM evaluates an LLM
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Training 2B-parameter AI systems to animal-level intelligence efficiently
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About 2 billion neurons, like parrots, dogs, and octopus.
How do we get a machine with 2B neurons / 10T parameters to get as smart as octopus, dogs, parrots, and crows with just a few months' worth of real-time training data? -
LLM Size vs Genome: Information Compression Limits
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Not really.
That would have to be compressed in a tiny amount of information.
A small 7B LLM requires 14GB.
Your entire genome fits in 800MB (uncompressed).
The difference between human and chimp genome is 1% of that, or 8MB.
Not enough to encode a significant structure. -
New AI Architectures for Efficient Learning Beyond Data Scaling
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Animals and humans get very smart very quickly with vastly smaller amounts of training data.
My money is on new architectures that would learn as efficiently as animals and humans.
Using more data (synthetic or not) is a temporary stopgap made necessary by the limitations of our