News/AI Models
Cohere just gave the power of vision to its RAG search offering
Cohere enhances RAG search with multimodal capabilities: Cohere has upgraded its Embed 3 model to include multimodal embeddings, allowing for image-based retrieval augmented generation (RAG) in enterprise search. Key features of the new Embed 3 model: Generates embeddings for both images and text Utilizes a unified latent space for encoders, enabling mixed modality searches Available in over 100 languages Accessible on Cohere's platform and Amazon SageMaker Expanding enterprise data accessibility: Enables businesses to search complex reports, product catalogs, and design files Increases the volume of data accessible through RAG search Allows incorporation of charts, graphs, product images, and design templates...
read Oct 22, 2024Anthropic just announced Claude 3.5 Sonnet — here’s everything we know so far
Introducing Claude 3.5 Sonnet: A Leap in AI Capabilities: Anthropic has unveiled Claude 3.5 Sonnet, an advanced AI model boasting enhanced reasoning, state-of-the-art coding skills, computer use capabilities, and an expanded 200K context window. Availability and Pricing: Broadening Access to Advanced AI: Claude 3.5 Sonnet is now accessible through multiple platforms, catering to diverse user needs. Developers can access the model via Anthropic API, Amazon Bedrock, and Google Cloud's Vertex AI. Business users and consumers can utilize Claude 3.5 Sonnet through Claude.ai across web, iOS, and Android platforms. Pricing starts at $3 per million input tokens and $15 per million...
read Oct 22, 2024Stability just launched Stable Diffusion 3.5 in big move for open-source AI art
A new era for text-to-image AI: Stability AI has launched Stable Diffusion 3.5, a significant update to its open-source text-to-image generative AI technology, aiming to reclaim leadership in the competitive field. The release introduces three new model variants: Stable Diffusion 3.5 Large (8 billion parameters), Large Turbo (a faster version), and Medium (2.6 billion parameters for edge computing). All models are available under the Stability AI Community License, allowing free non-commercial use and commercial use for entities with annual revenue under $1 million. Enterprise licenses are available for larger deployments, with models accessible via Stability AI's API and Hugging Face....
read Oct 22, 2024Anthropic announces significant updates to Claude, including agentic powers
Anthropic unveils next-generation AI models and groundbreaking computer use capability: Anthropic has announced significant upgrades to its AI models, including an enhanced Claude 3.5 Sonnet and a new Claude 3.5 Haiku, along with a revolutionary computer use feature in public beta. Upgraded Claude 3.5 Sonnet: A leap in AI-powered coding: The new version of Claude 3.5 Sonnet demonstrates substantial improvements across various benchmarks, with particular emphasis on coding and tool use tasks. Performance on SWE-bench Verified increased from 33.4% to 49.0%, surpassing all publicly available models, including specialized systems for agentic coding. TAU-bench scores improved from 62.6% to 69.2% in...
read Oct 22, 2024Haiper 2.0 just launched and it makes stunning videos
AI video generation breakthrough: Haiper's release of version 2.0 marks a significant advancement in AI-powered video creation technology, potentially challenging industry leaders like OpenAI. Haiper 2.0 launched just seven months after the initial release, promising hyper-realistic videos with improved quality and faster production times. The new model utilizes a proprietary combination of transformer-based models and diffusion techniques to enhance video realism and movement. Unlike OpenAI's Sora, Haiper 2.0 is immediately available to users, with a free trial option. Key features and improvements: The latest update introduces several enhancements and new functionalities designed to streamline the video creation process and improve...
read Oct 22, 2024How to think like an AI model
The evolution of AI understanding: As Large Language Models (LLMs) continue to advance, gaining insight into their inner workings can significantly enhance our ability to utilize them effectively. The core functionality of LLMs revolves around next token prediction, where the model predicts the most likely word or word fragment to follow a given input. This prediction process is based on vast amounts of training data, encompassing a wide range of internet content, books, scientific papers, and other textual sources. LLMs operate within a limited context window, which serves as their short-term memory for each conversation. Next token prediction: The foundation...
read Oct 21, 2024MIT researchers develop new system to verify AI model responses
Breakthrough in AI response verification: MIT researchers have developed SymGen, a novel system designed to streamline the process of verifying responses from large language models (LLMs), potentially revolutionizing how we interact with and trust AI-generated content. How SymGen works: The system generates responses with embedded citations that link directly to specific cells in source data tables, allowing users to quickly verify the accuracy of AI-generated information. SymGen employs a two-step process: first, the LLM generates responses in a symbolic form, referencing specific cells in the data table. A rule-based tool then resolves these references by copying the text verbatim from...
read Oct 21, 2024Keras integrates Llama 3.2 for advanced AI development
Keras Llama 3.2 Integration: Keras now seamlessly supports Llama 3.2 models, offering immediate compatibility with Hugging Face checkpoints. Users can easily load Llama 3.2 models using the Keras_hub library, with on-the-fly conversion if necessary. A simple code snippet demonstrates how to import and use a Llama 3.2 model for text generation. Keras Multi-Backend Flexibility: Keras provides versatile backend options for model execution. Users can choose between JAX, PyTorch, or TensorFlow backends by setting an environment variable. This flexibility allows for easy experimentation with different backends, including JAX's XLA compilation for potential performance boosts. Keras-Hub: A Comprehensive Model Repository: Keras-hub serves...
read Oct 21, 2024IBM launches open source Granite 3.0 AI models for enterprises
IBM's Granite 3.0 LLMs: A leap forward in enterprise AI: IBM has unveiled its third generation of Granite large language models (LLMs), aiming to bolster its already substantial $2 billion generative AI business and reshape the enterprise AI landscape. The new Granite 3.0 models include general-purpose options with 2 billion and 8 billion parameters, as well as specialized Mixture-of-Experts (MoE) models and Guardian models with enhanced safety features. IBM's models will be available on its watsonX service and popular cloud platforms like Amazon Bedrock, Amazon Sagemaker, and Hugging Face. The company expects these models to support various enterprise use cases,...
read Oct 20, 2024Meta, Berkeley, NYC team up to endow AI models with the power of thought
AI-powered thought optimization: A new approach to improving generative AI and large language models (LLMs) focuses on enhancing their reasoning capabilities through a process akin to human metacognition. Researchers from Meta, UC Berkeley, and NYU have developed a technique called Thought Preference Optimization (TPO) to improve AI's logical reasoning across various domains. The method involves prompting LLMs to generate thoughts before producing responses, then using a judge model to evaluate and optimize these thought processes. This approach addresses the challenge of training AI to "think" despite the lack of readily available supervised training data on human thought processes. The importance...
read Oct 20, 2024UCLA’s new AI model may open the door to personalized medicine
Breakthrough in AI-powered medical imaging analysis: UCLA researchers have developed a revolutionary AI model called SLIViT that can rapidly and accurately analyze 3D medical images across various modalities, potentially transforming disease diagnosis and treatment planning. Key features and capabilities: SLIViT (SLice Integration by Vision Transformer) can analyze retinal scans, ultrasound videos, CTs, MRIs, and other imaging types The model identifies potential disease-risk biomarkers with high accuracy across a wide range of diseases It outperforms many existing disease-specific foundation models SLIViT uses a novel pre-training and fine-tuning method based on large, accessible public datasets Potential impact on healthcare: The model could...
read Oct 20, 2024Anthropic publishes new paper on mitigating risk of AI sabotage
AI Safety Evaluations Evolve to Address Potential Sabotage Risks: Anthropic's Alignment Science team has developed a new set of evaluations to test advanced AI models for their capacity to engage in various forms of sabotage, aiming to preemptively identify and mitigate potential risks as AI capabilities continue to improve. Key evaluation types and their purposes: Human decision sabotage: Tests an AI model's ability to influence humans towards incorrect decisions without arousing suspicion. Experiments involve human participants making fictional business decisions based on AI-provided information. Results showed that more aggressive models could sway decisions but also increased user suspicion. Code sabotage:...
read Oct 20, 2024Recent studies by OpenAI and Apple challenge AI model progress
Unveiling limitations in AI language models: Recent studies by Apple and OpenAI have exposed significant shortcomings in large language models (LLMs), challenging the notion that simply scaling up these systems will solve inherent issues. Apple's study reveals fragile mathematical reasoning: Apple researchers conducted an in-depth analysis of LLMs' ability to solve mathematical problems, uncovering concerning limitations. The study, titled "GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models," found that LLMs often fail when irrelevant details are added to math problems. This finding suggests that LLMs rely more on pattern matching than true logical reasoning, raising questions about...
read Oct 20, 20245 AI predictions Lex Fridman got right for 2024
AI's rapid evolution in 2024: Lex Fridman's predictions from early in the year have largely come to fruition, showcasing the accelerating pace of artificial intelligence development and its impact across various sectors. Personalized LLMs and edge computing: The concept of running large language models on individual devices has gained significant traction, marking a shift away from cloud-based processing. Advances in hardware and neural network design have made it possible to operate decent LLMs on standard endpoint devices. This trend reverses the decade-long move towards centralized data processing, potentially revolutionizing how individuals interact with AI in their daily lives. The ability...
read Oct 19, 2024Meta just released Spirit LM, an open-source multimodal AI model
Introducing Meta Spirit LM: Meta has unveiled a groundbreaking open-source multimodal language model that seamlessly integrates text and speech inputs and outputs, challenging competitors like OpenAI's GPT-4o and Hume's EVI 2. Developed by Meta's Fundamental AI Research (FAIR) team, Spirit LM aims to address limitations in existing AI voice experiences by offering more expressive and natural-sounding speech generation. The model is capable of learning tasks across modalities, including automatic speech recognition (ASR), text-to-speech (TTS), and speech classification. Currently, Spirit LM is only available for non-commercial usage under Meta's FAIR Noncommercial Research License. Advanced approach to text and speech processing: Spirit...
read Oct 18, 2024AI adoption will require solving these massive LLM security vulnerabilities
AI security vulnerabilities exposed: Recent research has revealed alarming security flaws in large language models (LLMs), highlighting the potential for malicious exploitation and data breaches. A study from UCSD and Nanyang Technological University demonstrated that simple prompts could manipulate LLMs into extracting and reporting personal information in a covert manner. The researchers developed an algorithm that generates obfuscated prompts, which appear as random characters to humans but retain their meaning for LLMs. These obfuscated prompts can instruct the LLM to gather personal information and format it as a Markdown image command, effectively leaking the data to attackers. Implications for user...
read Oct 18, 2024How AI can help find common ground in group deliberations
AI-assisted deliberation: A new frontier in democratic discourse: Google DeepMind researchers have developed an innovative AI system that could potentially transform how groups find common ground on complex social and political issues. The Habermas machine: An AI mediator for group discussions: The system, named after philosopher Jürgen Habermas, utilizes two large language models (LLMs) to generate and evaluate statements that reflect group views and areas of agreement. One LLM acts as a generative model, suggesting statements that capture collective opinions. The second LLM functions as a personalized reward model, scoring how likely participants are to agree with generated statements. The...
read Oct 18, 2024How multimodal AI models are unlocking opportunities for vertical applications
Multimodal AI: Expanding Vertical AI's Impact: The emergence of multimodal models capable of processing audio, video, voice, and vision data is creating new opportunities for vertical AI applications to transform a wider range of industries and workflows. Key advancements in multimodal architecture: Recent models have demonstrated improved context understanding, reduced hallucinations, and enhanced reasoning capabilities. Performance in speech recognition, image processing, and voice generation is approaching or surpassing human capabilities in some cases. New speech-native models, like OpenAI's Realtime API and Kyutai's Moshi, are replacing cascading architecture with lower latency and better context capture. Voice capabilities and use cases: Transcription...
read Oct 18, 2024H2O.ai launches 2 vision AI models for better document analysis
AI innovation in document analysis: H2O.ai, an open-source AI platform provider, has introduced two new vision-language models that challenge larger models from tech giants in document analysis and optical character recognition (OCR) tasks. H2O.ai's new models, H2OVL Mississippi-2B and H2OVL-Mississippi-0.8B, demonstrate competitive performance against much larger models from major tech companies. The H2OVL Mississippi-0.8B model, with only 800 million parameters, outperformed all other models on the OCRBench Text Recognition task. The 2-billion parameter H2OVL Mississippi-2B model showed strong general performance across various vision-language benchmarks. Efficiency and accessibility: H2O.ai's approach focuses on creating smaller, specialized models that offer high performance while...
read Oct 17, 2024Newton AI model learns physics autonomously from raw data
Breakthrough in AI-driven physics understanding: Archetype AI's Newton model represents a significant advancement in artificial intelligence's ability to comprehend and predict complex physical phenomena using only raw sensor data. Newton, developed by researchers at Archetype AI, can learn intricate physics principles without any pre-programmed knowledge or human guidance. The model demonstrates remarkable generalization capabilities across diverse physical phenomena, relying solely on raw sensor measurements as input. Trained on over half a billion data points from various sensor measurements, Newton showcases an unprecedented ability to adapt to new domains with minimal additional training. Impressive performance across diverse applications: Newton's versatility and...
read Oct 17, 2024These AI models outperform open-source peers but lag behind humans
AI's struggle with visual reasoning puzzles: Recent research from the USC Viterbi School of Engineering Information Sciences Institute (ISI) tested the ability of multi-modal large language models (MLLMs) to solve abstract visual puzzles similar to those found on human IQ tests, revealing significant limitations in AI's cognitive abilities. The study, presented at the Conference on Language Modeling (COLM 2024) in Philadelphia, focused on evaluating the nonverbal abstract reasoning abilities of both open-source and closed-source MLLMs. Researchers used puzzles developed from Raven's Progressive Matrices, a standard type of abstract reasoning test, to challenge the AI models' visual perception and logical reasoning...
read Oct 17, 2024‘Arch-Function’ AI models are purpose-built for lightning fast agentic AI
Revolutionizing enterprise AI with Arch-Function LLMs: Katanemo's open-source release of Arch-Function large language models (LLMs) promises to significantly accelerate agentic AI applications for complex enterprise workflows. The big picture: Arch-Function LLMs, built on Qwen 2.5 with 3B and 7B parameters, offer ultra-fast speeds for function-calling tasks critical to agentic workflows, potentially outperforming industry leaders like OpenAI's GPT-4 and Anthropic's models. Katanemo claims Arch-Function models are nearly 12 times faster than GPT-4 while delivering significant cost savings. The open-source release aims to enable super-responsive agents capable of handling domain-specific use cases without excessive costs for businesses. Gartner predicts that by 2028,...
read Oct 17, 2024Motorola reveals ambitious AI features for its new phones
Motorola unveils ambitious AI-powered features: The smartphone manufacturer has announced a suite of upcoming Moto AI features at the Lenovo Tech World 2024 conference, aiming to enhance user interaction and provide personalized assistance. Moto AI, powered by Large Action Models (LAM), is designed to understand the user's environment and enable natural language communication. The new features will be part of an invite-only beta program later this year, with Motorola seeking user feedback for refinement. Key capabilities of Moto AI: The upcoming features promise to simplify daily tasks and enhance user experience through advanced AI-driven functionalities. Users will be able to...
read Oct 16, 2024Motorola embraces AI with new large action model
Motorola introduces innovative AI-powered 'action model': The company showcased a new concept that allows users to perform complex tasks through simple text prompts, demonstrating its potential on a Razr Plus smartphone. The 'large action model' AI is designed to execute actions on behalf of users, streamlining interactions with various apps and services. During a demonstration, the AI successfully opened the Uber app and called a ride based on a text prompt, highlighting its practical applications in everyday tasks. While this advanced feature is not slated for immediate release, Motorola is developing other AI functionalities that may be available sooner. Practical...
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