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  • šŸ¤– Nvidia Quietly Drops New AI Model That Outperforms Everyone

šŸ¤– Nvidia Quietly Drops New AI Model That Outperforms Everyone

PLUS: Salesforce CEO Marc Benioff Explains The AI Agent Revolution, Merging AI Models to Combine Their Strengths

Welcome back AI enthusiasts!

In todayā€™s AI Report:

  • šŸ’ØNvidia Quietly Drops New AI Model That Outperforms Everyone

  • šŸŽ™Salesforce CEO Marc Benioff Explains The AI Agent Revolution

  • šŸ“ŠMerging AI Models to Combine Their Strengths

  • šŸ› Trending Tools

  • šŸ’°Funding Frontlines

  • šŸ’¼Whoā€™s Hiring?

Read Time: 3 minutes

šŸ—žRECENT NEWS

NVIDIA

šŸ’ØNvidia Quietly Drops New AI Model That Outperforms Everyone

Image Source: Canvaā€™s AI Image Generators/Magic Media

Nvidia quietly released a new AI model called Llama-3.1-Nemotron-70B-Instruct, which outperforms industry leaders across various benchmarks.

Key Details:
  • Nvidiaā€™s Nemotron Instruct was built using Llama 3.1 70B, an open-source Large Language Model (LLM) developed by Metaā€™s AI team.

  • LLMs are AI models pre-trained on massive amounts of data to generate human-like text.

  • Nvidia fine-tuned the LLM using Reinforcement Learning From Human Feedback (RLHF).

  • RLHF is a training method that uses human feedback to teach LLMs to self-learn more efficiently and align with human preferences.

  • Nvidiaā€™s Nemotron Instruct outperforms OpenAIā€™s GPT-4o (ā€œoā€ for ā€œomniā€) and Anthropicā€™s Claude 3.5 Sonnet across various benchmarks:

    1. Arena-Hard-Auto: Contains 500 diverse and difficult user queries to test the quality of LLM responses.

    2. AlpacaEval 2.0: Measures how well LLMs can follow instructions.

  • While not perfect, these benchmarks provide the most accurate comparisons of LLMs. These impressive results catapult Nvidia to the forefront of AI research.

AI INDUSTRY INSIGHTS

šŸŽ™Salesforce CEO Marc Benioff Explains The AI Agent Revolution

Image Source: Rapid Response (RR)/ā€œMarc Benioff: Salesforce Can Beat Microsoft in AIā€/Screenshot

Salesforce CEO Marc Benioff discussed how the ā€œAI Agent revolution is realā€ and as exciting as the cloud computing movement and the mobile device wave.

Key Details:
  • When talking about AIā€™s potential, Benioff said, ā€œIā€™ve never been more excited about anything at Salesforce, maybe in my career.ā€

  • Heā€™s referring to Salesforceā€™s Agentforce, which helps companies build AI agents that work together with humans to drive customer success and enhance existing workflows.

  • ā€œI think weā€™ll have over one billion AI agents running within the next 12 months,ā€ he added.

  • However, Benioff also warned that companies ā€œhave been told things about enterprise AI, maybe AI overall, that arenā€™t true.ā€

  • He said that leaders of new companies, such as OpenAIā€™s CEO Sam Altman, ā€œclaim that AI cures cancer and AI solves climate change. That may be possible in the future, but thatā€™s not where weā€™re at today.ā€

  • ā€œLLMs are great, but theyā€™re not AGI. Theyā€™re a constrained AI model you can extend, complement, and make very accurate.ā€

  • Artificial General Intelligence (AGI) is a theoretical concept where AI achieves human-level learning, perception, and cognitive flexibility.

  • ā€œItā€™s about managing expectations while harnessing AIā€™s capabilities,ā€ Benioff explained.

Why Itā€™s Important:
  • AI agents can handle multiple customer interactions simultaneously, significantly reducing response times and increasing the efficiency of customer service operations.

  • This allows businesses to handle higher volumes of inquiries without compromising on the quality of service.

šŸšØWatch Benioffā€™s 25-minute interview here.

šŸ©ŗ PULSE CHECK

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AI RESEARCH

šŸ“ŠMerging AI Models to Combine Their Strengths

Image Source: Acree AI and Liquid AI/ā€œMerging in a Bottle: Differentiable Adaptive Merging (DAM) and The Path From Averaging to Autonomyā€/Screenshot

Researchers from Acree AI and Liquid AI developed Differentiable Adaptive Merging (DAM), which involves merging multiple AI models to combine their strengths.

Merging multiple AI models isnā€™t easy because of the various training methods and fine-tuning actions tailored to each AI model. So, itā€™s an expensive process that requires specialized knowledge, repeated refinement, and computing power.

DAM is a cost-effective solution that leverages an Adaptive Merging Approach to optimize the combination of AI models through Scaling Coefficients.

In simple terms, DAM helps merge multiple AI models into a bigger and better AI model. Itā€™s like merging several smaller puzzles into a bigger and better puzzle.

Adaptive Merging Approach means that DAM can adjust to different situations (i.e., itā€™s like combining several different puzzle pieces together until they fit).

Scaling Coefficients are weights that determine the influence of each AI model when theyā€™re combined using DAM (i.e., itā€™s like giving each puzzle piece a different importance level).

šŸ› TRENDING TOOLS

šŸ’­Code2AI turns your ideas into code.

šŸ“±Taplio grows your personal brand on LinkedIn.

šŸ‹Lime is your AI-powered data research assistant.

šŸ’¬insightbase enables you to chat with your database using AI.

āš™ļøGradio 5.0 builds, deploys, and shares Machine Learning (ML) apps.

šŸ”®Browse our always Up-To-Date AI Tools Database.

šŸ’°FUNDING FRONTLINES

  • Fable secures a $25M Series B to protect digital accessibility in the age of AI.

  • Live Aware Labs closes a $4.8M Seed Round for its AI-powered gamer feedback platform.

  • Lightmatter raises a $400M Series D for photonic data centers that use light signals instead of electric signals to transmit data.

šŸ’¼WHOā€™S HIRING?

  • Amazon (Seattle, WA): Data Engineer Intern, Summer 2025

  • Adobe (San Jose, CA): Data Scientist Intern, Firefly, Summer 2025

  • Zoox (Foster City, CA): AI Agent Behavior Software Engineer Intern/Co-Op, Summer 2025

  • Boston Consulting Group {BCG} (Los Angeles, CA): AI Software Engineer Intern, Summer 2025

  • Bank of America {BofA} (New York City, NY): Risk Analysis Analyst, Market Behavior Analytics, Entry-Level

šŸ¤–PROMPT OF THE DAY

CUSTOMERS

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šŸ“’FINAL NOTE

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ā¤ļøTAIP Review of The Day

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