šŸ¤– OpenAI Partners With TIME

PLUS: Hugging Face Updates Open LLM Leaderboard, Googleā€™s New Gemma 2

Welcome back AI enthusiasts!

In todayā€™s AI Report:

  • ā°OpenAI Partners With TIME

  • šŸ†Hugging Face Updates Open LLM Leaderboard

  • āš™ļøGoogleā€™s New Gemma 2

  • šŸ› 5 Trending Tools

  • šŸ’°Venture Capital Updates

  • šŸ’¼Whoā€™s Hiring?

Read Time: 3 minutes

šŸ—žRECENT NEWS

OPENAI

ā°OpenAI Partners With TIME

Image Source: Amir Cohen/Vox Screenshot

OpenAI partnered with TIME in a multi-year content deal and strategic partnership to bring TIMEā€™s trusted journalism to OpenAIā€™s ChatGPT.

Key Details:
  • OpenAI will access current and historical content from TIMEā€™s extensive archives covering the last 101 years to enhance ChatGPTā€™s historical training datasets.

  • When ChatGPT responds to a userā€™s query with TIME content, itā€™ll feature a citation and direct link back to the original source.

  • TIME COO Mark Howard explained: ā€œThis partnership with OpenAI advances our mission to expand access to trusted information globally.ā€

  • TIME will access OpenAIā€™s products and services to develop tailored AI offerings for its readers.

  • OpenAI COO Brad Lightcap expressed: ā€œWeā€™re partnering with TIME to support reputable journalism by providing proper attribution to original sources.ā€

Why Itā€™s Important:
  • Eight established U.S. newspapers recently filed a lawsuit against OpenAI and Microsoft, accusing the technology giants of illegally leveraging copyrighted articles to train AI models.

  • OpenAI should change the companyā€™s name to ā€œPartnerAI.ā€ They seem to be strategically partnering and acquiring publications to avoid legal disputes.

šŸ©ŗ PULSE CHECK

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HUGGING FACE

šŸ†Hugging Face Updates Open LLM Leaderboard

Image Source: Canva AI Image Generator

Hugging Face introduced new benchmarks, metrics, and evaluation methods to measure the performance of Large Language Models (LLMs).

Key Details:
  • The Open LLM Leaderboard hosted over 2 million unique website visits and evaluated around 300,000 community member submissions and discussions.

  • This popularity, paired with LLM advancements, made it difficult for the current Open LLM Leaderboard to differentiate between AI models effectively.

  • For example, developers leveraged similar benchmark datasets to train their LLMs, leading to dataset contamination or ā€œoverfitting.ā€

  • This ā€œoverfittingā€ enabled LLMs to memorize specific problems from benchmarks instead of learning general problem-solving skills to apply concepts and perform well on unseen data.

  • Hugging Face added new benchmarks to address ā€œoverfittingā€ (e.g., MMLU-Pro, GPQA, MuSR, MATH, IFEval, and BBH) and new metrics for ranking LLMs using normalized scores.

Why Itā€™s Important:
  • Measuring an LLMā€™s performance is difficult. LLMs are constantly evolving and approaching human-level performance on most tasks, which leads to benchmark saturation and metric contamination.

  • Updating the Open LLM Leaderboard creates a universal evaluation method with new benchmarks and metrics to rank LLMs accurately.

šŸšØCheck out the Open LLM Leaderboard V2 here.

AI RESEARCH

āš™ļøGoogleā€™s New Gemma 2

Google unveiled Gemma 2, a series of open-source language models offering researchers and developers best-in-class performance across different hardware.

Gemma 2 was trained on a massive dataset of text data containing trillions of tokens:

  1. The larger 27B parameter model was trained on a whopping 13 trillion tokens.

  2. The smaller 9B parameter model was trained on a still-impressive 8 trillion tokens.

Tokens are the smallest units of data used by an AI model to process and generate text. Similarly, we break down sentences into words or characters. You can think of tokens as syllables.

However, tokens represent many components beyond just alphabetical characters, like punctuation or sentence boundaries. You can experiment with OpenAIā€™s tokenizer here.

Gemma 2 is designed to require fewer computing resources, which allows it to run on smaller devices and reduce deployment costs. It supports various tools and frameworks (e.g., TensorFlow, PyTorch, JAX, and Keras), giving developers flexibility.

šŸ› TRENDING TOOLS

šŸ’›ApyHub builds, tests, and documents API development.

šŸ’¬Question Base automates repetitive questions in Slack.

šŸŽØGradient Generator creates beautiful gradients to match your design.

šŸ•øSider empowers you to chat, write, read, and translate on any webpage.

šŸŽøJamahook instantly finds the perfect musical elements for the song youā€™re working on.

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

šŸ’°VENTURE CAPITAL UPDATES

  • Fetcherr lands a $90M Series B to get airlines on board with dynamic pricing.

  • Dust grabs a $16M Series A to deploy enterprise AI assistants connected to internal data.

  • Liminal raises a $5M Seed Fund to enable customers to deploy GenAI for regulatory compliance and data security.

šŸ’¼WHOā€™S HIRING?

  • Ventas (Chicago, IL): Software Engineering Intern, Summer 2025

  • Morgan Stanley (New York, NY): 2025 Technology Summer Analyst Program

  • Zoom (San Francisco, CA): AI/ML Speech Engineer, New Grad

  • Meta (Menlo Park, CA): Product Security Engineer, Entry-Level

  • Anyscale (Remote): Consulting Engineer

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CUSTOMER SERVICE

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Include specific examples or case studies of businesses thatā€™ve successfully integrated chatbots to enhance customer satisfaction and operational efficiency.

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šŸ“’FINAL NOTE

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