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Today:

• Anthropic CEO Predicts AGI 2026

• Mistral Unveils AI for Phones and Laptops

• Microsoft's Diff Transformer Boosts LLM Focus

• Amazon Joins Google, Microsoft in Nuclear Push

• Google.org Grants $15M for AI Training

ANTHROPIC CEO : AGI BY 2026, Happiness, Immortality Escape Velocity and Machines of Loving Grace....

Dario Amodei, CEO of Anthropic, explores the transformative potential of powerful AI in his essay, "Machines of Loving Grace." While previously known for emphasizing the risks of AI, Amodei now highlights its radical benefits across biology, neuroscience, mental health, economic development, and governance. 

He envisions AI surpassing Nobel Prize-level intelligence, autonomously solving complex problems, and driving breakthroughs like curing diseases and extending human lifespans. Amodei also addresses societal challenges, such as equitable access to AI's advancements and managing its integration with human and economic systems, urging careful, swift development.

WATCH THE VIDEO ON YOUTUBE

Mistral Unveils AI for Phones and Laptops

Mistral, a French AI startup, has launched "Les Ministraux," its first generative AI models for use on laptops and phones. These models, called Ministral 3B and Ministral 8B, offer low-latency performance for tasks like text generation, translation, and analytics on edge devices. With a 128,000-token context window, the models handle large inputs, about the length of a 50-page book. 

While the Ministral 8B is available for research, commercial use requires a license. Mistral aims to compete with AI giants like OpenAI, focusing on privacy and efficiency, and has begun generating revenue after raising $640 million.

Microsoft's Diff Transformer Boosts LLM Focus

Microsoft and Tsinghua University researchers developed the Differential Transformer, a new large language model (LLM) architecture that improves attention to relevant information while reducing noise. Traditional Transformers struggle with long contexts, often losing focus and creating errors. Diff Transformer solves this by using differential attention, which compares two attention maps to amplify key inputs while filtering out irrelevant ones. 

Experiments showed that Diff Transformer outperforms classic Transformers across various tasks and requires fewer resources. The architecture shows potential for improving applications like in-context learning and retrieval-augmented generation, with plans to extend its use to multimodal data.

Amazon Joins Google, Microsoft in Nuclear Push

Amazon has signed agreements to invest in nuclear energy, joining other tech giants like Google and Microsoft. The deals include building small modular reactors (SMRs), which are quicker to deploy and have smaller footprints than traditional reactors. These reactors will help Amazon meet its sustainability goal of being carbon-neutral by 2040. 

The AI boom has significantly increased energy consumption for tech companies, straining their environmental goals. Data centers powering AI, such as ChatGPT, are responsible for rising electricity use, prompting companies to turn to nuclear power as a cleaner energy solution for their operations.

Google.org Grants $15M for AI Training

Google.org has announced $15 million in grants to train U.S. public sector workers in AI skills. The Partnership for Public Service will receive $10 million to establish the Center for Federal AI, which will launch in 2025 to train federal employees in responsible AI use. InnovateUS will receive $5 million to expand AI training for state and local government workers, aiming to reach 100,000 people across 30 states. 

This funding supports Google.org's goal of improving government services through AI while addressing skills gaps and promoting effective AI use in public service.

🧠RESEARCH

nvidia/Llama-3.1-Nemotron-70B-Instruct

NVIDIA's Llama-3.1-Nemotron-70B-Instruct model excels in user query response accuracy, topping three alignment benchmarks as of October 2024. Trained using reinforcement learning, it improves general instruction-following, reaching high scores in language model benchmarks. It's available for free inference with an OpenAI-compatible API on NVIDIA's platform.

CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos

CoTracker simplifies video point tracking by allowing users to upload short .mp4 videos for quick processing. After submitting the video, users can either track a grid of points or manually select specific points to track. The tool delivers fast, efficient results and offers additional resources through its GitHub repository.

MTU-Bench: A Multi-granularity Tool-Use Benchmark for Large Language Models

MTU-Bench is a new multi-granularity tool-use benchmark designed to evaluate large language models (LLMs) in five tool-use scenarios, addressing limitations of existing benchmarks. It avoids costly GPT-based evaluations by relying on ground truth comparisons. The benchmark enhances LLMs' tool-use abilities through the MTU-Instruct dataset, simulating real-world tasks. Results demonstrate its effectiveness, and code will be available on GitHub.

LVD-2M: A Long-take Video Dataset with Temporally Dense Captions

LVD-2M is a dataset designed to improve long video generation by offering 2 million long-take videos, each over 10 seconds with temporally dense captions. It addresses limitations in previous datasets that focused on short clips, providing videos with continuous motion and diverse content. This dataset supports advancements in generating dynamic, long videos.

EchoPrime: A Multi-Video View-Informed Vision-Language Model for Comprehensive Echocardiography Interpretation

EchoPrime is a multi-view vision-language model designed to improve echocardiography interpretation by integrating information from multiple ultrasound videos. Trained on over 12 million video-report pairs, it uses contrastive learning and an anatomic attention model to accurately map echocardiographic views to heart structures. EchoPrime outperforms single-view models on 23 benchmarks, offering a more comprehensive and automated assessment for cardiac diagnostics.

🛠️TOP TOOLS

Gradio 5.0 - Build & share delightful machine learning apps

Code2.AI - Turn your ideas into code

Athina - Prototype, experiment, evaluate, and monitor LLM-powered apps.

HeyGen - Create your own or choose from our library of AI avatars and voices - in over 175 languages.

Runway - A new frontier for fast, high-fidelity, controllable video generation.

📲SOCIAL MEDIA

🗞️MORE NEWS

• The National Archives plans to launch "Archie," an AI chatbot powered by Google Gemini. Employees express concerns over AI's role in preserving history, fearing inaccuracies. The AI is intended to enhance public access and productivity.

• Apple launched a new iPad mini featuring AI capabilities like advanced writing tools and an improved Siri assistant. Powered by the A17 Pro chip, the device enhances performance by 30%, starting at $499, with pre-orders available now.

• Meta revealed its latest AI hardware innovations at the 2024 Open Compute Project Summit, highlighting open-source designs like the Catalina rack for AI workloads. These scalable, high-powered systems aim to foster collaboration and enhance AI infrastructure performance.

• Elias Torres, former HubSpot VP and Drift co-founder, has launched Agency, an AI startup designed to automate tasks for customer success managers (CSMs). The company raised $12 million in seed funding, led by Sequoia and HubSpot Ventures.

• Cognizant has added multi-agent functionality to its Neuro AI platform, allowing enterprises to independently create AI applications without coding. The platform uses multiple AI agents to guide businesses through ideation, data generation, and application setup, enhancing generative AI adoption.

• AI is improving flood forecasting, but despite accurate predictions, challenges in managing extreme weather events remain. Experts highlight the need for better communication, investment in infrastructure, and climate change preparedness to reduce disaster risks and enhance response efforts.