Epigenetics Update - Genome modelling and design across all domains of life with Evo 2 go.nature.com/40Fhtm6

Patrick D. Hsu and Brian L. Hie reporting in Nature

#Epigenetics #FoundationModels
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Empower your research with high-res epigenetic insights at epigenometech.com

🧠 El verdadero avance en robótica son los modelos fundacionales, no el hardware

La IA física, o IA encarnada, es la próxima evolución para crear sistemas autónomos.

https://thenewstack.io/physical-ai-models-frontier/

#FoundationModels #EmbodiedAI #Robotics #RoxsRoss

The Model That Knows Too Much: How AI Can Leak What It Learned
youtu.be/pwA5nASJpoo #Cybersecurity #ArtificialIntelligence #AIsecurity #ModelInversionAttacks #DataPrivacy #MachineLearning #AISafety #Infosec #DigitalRisk #FoundationModels #DataProtection #CyberRisk

A huge thank you to #LeonardHackel for such a thought-provoking and forward-looking presentation! 🙌

#FoundationModels #AI #EarthObservation #Geospatial #MixtureOfExperts

New Epigenome Technologies Blog post!

"Fine-turning Borzoi with Single-Cell Epigenetics"

Start reading on our blog bit.ly/4cS72CS and read all the details on our new Substack page bit.ly/40sDTXD

#EpigenomeTech #Blog #Epigenetics #SingleCells #FoundationModels

SOOFI Launches: Europe’s Path Towards Its Own AI Language Models - L3S Research Center With SOOFI (Sovereign Open Source Foundation Models), one of the most ambitious initiatives to strengthen European AI sovereignty is now underway. The project aims to develop an open AI language model...

Europe’s competitiveness will depend on linking its foundation models with industrial applicability, governance standards, and sectoral integration.

SOOFI: ~100B parameter, reasoning model and agentic applications.
#SovereignAI #EuropeanAI #FoundationModels

Europas Wettbewerbsfähigkeit hängt künftig davon ab, eigene Foundation-Modelle mit industrieller Anwendbarkeit, Governance-Standards und sektoraler Integration zu verbinden.
Mit SOOFI startet eine der ambitioniertesten europäischen Initiativen für souveräne Open-Source-Foundation-Modelle – […]

Data Poisoning — The Silent Sabotage of AI
youtu.be/J-tsemViDXk #Cybersecurity #ArtificialIntelligence #AIsecurity #DataPoisoning #MachineLearning #AIrisk #AISafety #ModelSecurity #FoundationModels #CyberRisk #Infosec #DigitalTrust

New Epigenome Technologies Blog post! bit.ly/4rfD3JA

"What Can Epigenomic Foundation Models Reveal About Biology?"

Part 2: Modeling DNA Methylation

#EpigenomeTech #Blog #FoundationModels #DNAm

AWS Launches SageMaker Inference for Custom Nova Models AWS has launched SageMaker Inference for custom Nova models, completing a full fine-tuning-to-deployment pipeline for Nova Micro, Nova Lite, and Nova 2 Lite.

winbuzzer.com/2026/02/17/a...

AWS Launches SageMaker Inference for Custom Nova Models

#AI #Amazon #AmazonWebServicesAWS ##CloudComputing #EnterpriseAI #AgenticAI #FoundationModels #AIInference #NovaMicro #NovaLite #AmazonNova #AmazonSagemaker #Nova2Lite

This study introduce AlphaOcean, a foundation framework for digital-ocean intelligence that learns a shared operational multimodal representation of the ocean state from heterogeneous observations.
doi.org/10.59717/j.x...
#alphaocean #FoundationModels #marinescience

Meeting Minutes: Pragmatic AI: Foundation models running entirely on-device. Apple's exclusive iOS 26 AI. No other platform can do this.
#FoundationModels #iOS26 #Exclusive #Simple #DataPrivacy
#OnDevice #iOS26 #Privacy #Productivity
#Focus #Minimalism #Private

apps.apple.com/gb/app/meeti...

🤖 Hybrid AI done right!

Peter Friese shows how to combine on-device speed with cloud-scale power using #AppleIntelligence, #FoundationModels & Firebase AI Logic.
Architecture, fallbacks, real strategies.

A must-see talk for modern iOS engineers 🚀

mobilewarsaw.pl/104?s=b

Theme: Geospatial Foundation Models for Advancing Remote Sensing of Environment
Submission deadline: 30 June 2026

More details & submission guidelines:
www.sciencedirect.com/special-issu...

#RemoteSensing #EarthObservation #FoundationModels #GeoAI #MachineLearning

Kudos to the authors Xinhao Mei, Varun Nagaraja, et al.
Read the paper: arxiv.org/pdf/2601.12594

#ai #audioai #research #foundationmodels #equalyzai

Image from article in Radiology: Artificial Intelligence

Foundation models have expanded from text-only large language models to large multimodal models radiologyai.substack.com/p/from-narrow-ai-to-gene... @uniregensburg.bsky.social #FoundationModels #mutlimodal #ML

biomeStat - The Only Tool A Scientist Will Ever Need Genomics. Flow Cytometry. Statistics. biomeStat handles it all.

AMW is pleased to announce the launch of biomeStat! Now access all bioinformatics tools on one platform. biomestat.com

#foundationmodels #aixbiologyAccess

Image from article in Radiology: Artificial Intelligence

"AI is evolving from narrow algorithms to more generalist systems built on foundation models" radiologyai.substack.com/p/from-narrow-ai-to-gene... @uniregensburg.bsky.social #FoundationModels #DeepLearning #MachineLearning

New Epigenome Technologies Blog post! bit.ly/3Z42Qbo

"What Can Epigenomic Foundation Models Reveal About Biology?"

Welcome to the first in a series of blogs, which focuses on applying foundation model techniques (or "deep learning") to epigenetics datasets

#Epigenetics #Blog #FoundationModels

Image from article in Radiology: Artificial Intelligence

"AI is evolving from narrow algorithms to more generalist systems built on foundation models" radiologyai.substack.com/p/from-narrow-ai-to-gene... @uniregensburg.bsky.social #FoundationModels #DeepLearning #MachineLearning

12/12
Paper: arxiv.org/pdf/2507.11569
Code: t.co/F76HkJOIBT

#FoundationModels #MedicalImaging #BreastMRI #ImageRegistration #ZeroShot #SAM #DINOv2 #MedAI

Image from article in Radiology: Artificial Intelligence

"[T]here is a shift from isolated tools to frameworks that promise to orchestrate the full radiology workflow" radiologyai.substack.com/p/from-narrow-ai-to-gene... @uniregensburg.bsky.social #FoundationModels #DeepLearning #mutlimodal

Getting Started with Apple Foundation Models for Local AI in SwiftUI - Ottorino Bruni Learn how to use Apple Foundation Models for on-device AI in SwiftUI apps. Build local, private, and intelligent features without external APIs

🤖 Getting Started with Apple Foundation Models for Local AI in SwiftUI On-device generative AI in iOS 18+ → summarization, classification, creative writing, zero cloud, full privacy & low latency #swiftui #appleintelligence #foundationmodels #localai #iosdev www.ottorinobruni.com/getting-star...

My first iOS app is live on the App Store🎉

SparkyTales lets parents & kids create animal characters and bedtime stories using Apple’s Foundation Models, fully on-device & offline.

Download: apps.apple.com/us/app/spark...

#SwiftUI #AppleIntelligence #FoundationModels

Apple Turns to Google Gemini to Power AI Enhanced Siri - WinBuzzer Apple has announced a multi-year partnership with Google to power Siri using Gemini AI, launching with iOS 26.4 in March or April 2026 for approximately $1 billion annually.

winbuzzer.com/2026/01/13/a...

Apple Turns to Google Gemini to Power AI Enhanced Siri

#Apple #Google #Siri #AppleIntelligence #GoogleGemini #LargeLanguageModels #AIPartnerships #VoiceAssistants #AIAssistants #iPhone #iOS #FoundationModels #OnDeviceAI #BigTech #AIPrivacy #SearchEngines

Prompting an on-device foundation model | Apple Developer Documentation Tailor your prompts to get effective results from an on-device model.

🤖 𝑃𝑟𝑜𝑚𝑝𝑡𝑖𝑛𝑔 𝑎𝑛 𝑜𝑛-𝑑𝑒𝑣𝑖𝑐𝑒 𝑓𝑜𝑢𝑛𝑑𝑎𝑡𝑖𝑜𝑛 𝑚𝑜𝑑𝑒𝑙

Critical strategies to reduce hallucinations and maximize performance on smaller on-device models.

#AI #FoundationModels #iOS

developer.apple.com/documentatio...

Foundation Models: The Revolutionary AI Technology Transforming Machine Learning Foundation Models: The Revolutionary AI Technology Transforming Machine Learning Table of Contents * What Are Foundation Models? * Key Characteristics * Popular Foundation Model Examples * Real-World Applications * Benefits and Challenges * Frequently Asked Questions What Are Foundation Models? Foundation models represent a groundbreaking paradigm shift in artificial intelligence development, fundamentally changing how we approach machine learning tasks. These sophisticated AI systems are trained on vast, immense datasets encompassing billions or even trillions of data points, enabling them to perform a remarkably broad range of general tasks across multiple domains. Coined by researchers at Stanford University's Center for Research on Foundation Models in 2021, the term "foundation model" specifically refers to any AI model trained on broad data using self-supervision at scale, capable of being adapted to numerous downstream tasks through fine-tuning or other adaptation methods. Key Characteristics of Foundation Models Massive Scale and Training Unlike traditional machine learning models trained on smaller, task-specific datasets, foundation models utilize massive computational resources and enormous datasets. Most advanced foundation models contain tens of billions to hundreds of billions of parameters, requiring sophisticated infrastructure and extended training periods using powerful GPUs. Transfer Learning Capabilities Foundation models excel at transfer learning—applying knowledge learned from one task to solve entirely different problems. This flexibility distinguishes them from conventional AI systems that perform only specific, predefined functions. Self-Supervised Learning These models typically employ self-supervised learning techniques, allowing them to discover inherent patterns and correlations in unlabeled data without requiring extensive human annotation, significantly reducing development costs and time. Popular Foundation Model Examples Large Language Models (LLMs) GPT (Generative Pre-trained Transformer) developed by OpenAI represents one of the most prominent foundation model families. GPT-4, the latest iteration, successfully passed the Uniform Bar Examination with a 76% score and powers ChatGPT, demonstrating exceptional natural language understanding and generation capabilities. BERT (Bidirectional Encoder Representations from Transformers), released by Google in 2018, was among the first widely-adopted foundation models, trained on plain text and Wikipedia using 3.3 billion tokens. Claude by Anthropic and PaLM 2 by Google represent newer generation foundation models with enhanced reasoning, multilingual capabilities, and improved safety features. Multimodal Foundation Models DALL-E and Stable Diffusion exemplify text-to-image foundation models that generate high-quality visual content from textual descriptions, revolutionizing creative industries. Real-World Applications Natural Language Processing Foundation models power advanced NLP applications including question answering, text summarization, language translation, sentiment analysis, and conversational AI assistants. Healthcare Innovation In healthcare, foundation models assist with medical literature searches, patient visit summarization, clinical trial matching, drug discovery acceleration, and medical image analysis—significantly improving diagnostic accuracy and research efficiency. Software Development Code generation models like GitHub Copilot, powered by foundation models, help developers write, debug, and optimize code across 116+ programming languages, dramatically accelerating software development cycles. Computer Vision Foundation models enable sophisticated image classification, object detection, facial recognition, and autonomous vehicle navigation systems with unprecedented accuracy. Benefits and Challenges Advantages for Enterprises * Accelerated Time-to-Value: Organizations can rapidly customize pre-trained models instead of building from scratch * Cost Efficiency: Eliminates expensive pretraining phases requiring massive computational resources * Baseline Performance: Proven accuracy and reliability provide high-quality starting points * Broad Applicability: Single models adapt to multiple use cases across industries Considerations and Risks * Bias Concerns: Models may inherit biases present in training data, potentially perpetuating unfair outcomes * Computational Costs: Deployment still requires significant GPU resources and energy consumption * Hallucinations: Models can generate plausible-sounding but factually incorrect information * Data Privacy: Training data may include sensitive information raising intellectual property concerns * Environmental Impact: Energy-intensive training contributes to carbon emissions Frequently Asked Questions What's the difference between foundation models and traditional AI? Traditional AI models are typically trained for specific tasks using smaller datasets, while foundation models are trained on massive, diverse datasets and can be adapted to multiple tasks through transfer learning. Are all large language models foundation models? Yes, large language models (LLMs) like GPT, BERT, and Claude are types of foundation models specifically designed for natural language processing tasks, but foundation models also include image, audio, and multimodal systems. How expensive is it to train a foundation model? Training advanced foundation models can cost hundreds of millions of dollars due to computational infrastructure requirements, extended training times, and massive dataset processing needs. Can small businesses use foundation models? Absolutely! Small businesses can leverage existing foundation models through APIs or open-source options, adapting them to specific needs through fine-tuning without bearing massive training costs. What is the future of foundation models? The future includes more efficient training methods, improved multimodal capabilities, enhanced safety features, and broader accessibility through open-source initiatives and optimized inference techniques. Found This Article Valuable? Share this comprehensive guide on foundation models with your network and help others understand this transformative AI technology! Share on Twitter Share on LinkedIn Share on Facebook Conclusion Foundation models represent a transformative breakthrough in artificial intelligence, offering unprecedented versatility and power across countless applications. As these systems continue evolving, they promise to reshape industries, accelerate innovation, and unlock new possibilities in human-AI collaboration. Understanding foundation models is essential for anyone involved in technology, business, or research, as they increasingly become the backbone of modern AI infrastructure. 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Learn about their capabilities, applications, benefits, and challenges.", "image": "https://sspark.genspark.ai/cfimages?u1=YFllz5QZgeGPJFnDRNtjejwitVMp4HnELUp6siFm1A9ETkKymJFNgp9zd9IpJEOx7bLDFijQnjyFQ6ykIoCyd%2FScQej02DS8leSCKVEEYbXamtpfZ7FlU9U4Wh81iVkBZb%2FmY68E%2BC8qYArXWGakXsdMkyo3Tg%3D%3D&u2=MVwakz%2BPt%2BibCeKg&width=2560", "author": { "@type": "Organization", "name": "YourSiteName" }, "publisher": { "@type": "Organization", "name": "YourSiteName", "logo": { "@type": "ImageObject", "url": "https://www.yoursite.com/logo.png" } }, "datePublished": "2025-12-23", "dateModified": "2025-12-23", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://www.yoursite.com/foundation-models" } } Thank you for reading. Visit our website for more articles: https://www.proainews.com

Foundation Models: The Revolutionary AI Technology Transforming Machine Learning #FoundationModels #ArtificialIntelligence #MachineLearning #AIInnovation #DataScience

We believe this is a key step for robust 3D understanding and cross-view reasoning.

Check out the code and visuals on our project page! Co-authored with Leo Segre and Shai Avidan.

#ComputerVision #FoundationModels #3D #DINO #SAM #CLIP

#FoundationModels — #AI systems trained on massive data sets — have the potential to transform scientific discovery and innovation.

Our new report examines how these models could be used to support the U.S. Department of Energy's mission.

Learn more: https://ow.ly/WqO250XKuF2