Ben Hamner
@benhamner
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Sumble co-founder and CTO. Learning high-quality, structured data about the world. Formerly @kaggle
SF
Joined March 2009
Wordle xxx 1/6 🟩🟩🟩🟩🟩 Get Wordle right on your first guess using the daily ⬛🟨🟩 tweet distribution
kaggle.com
Explore and run machine learning code with Kaggle Notebooks | Using data from Wordle Tweets
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Excited to share more publicly what @benhamner and I have been working on: https://t.co/QXvodhsM5e We are building a knowledge graph for GTM data & have early customers such as @elastic, @figma and @Snowflake
techcrunch.com
The founders of machine learning community Kaggle are trying to upend the crowded sales prospecting market with AI. And they're making headway.
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WOW - cold inbound hiring processes are the worst I've ever seen it: - Huge volume of applications (probably triggered automatically) - Large volume of fake resumes - Extensive use of AI assistants in phone screens
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You could release a crazy stat on the number of times (and number of employees) ClosedAI companies have downloaded open models from HuggingFace
@KamStaszewski All closed-source frontier labs use tons of open-source all over the stack, starting from python, @PyTorch, @huggingface all the way down to RoPE, GQA, flash-attention, or any tiny improvements released by open-source players. The whole transformers architecture (the T in gpT)
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Assumptions: 8 billion people * 20k spoken/written words per day * 1.3 tokens per word
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This is around 5x the ~200 trillion natural language tokens humans generate every month
Google is processing 980 trillion+ monthly tokens across our products and APIs (up from 480T in May) 🤯 No slowdown in sight, intelligence is everywhere.
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Kaggle launched an LLM eval product https://t.co/lJ8uSI2HmE This has the potential solve the biggest challenge in the LLM ecosystem: strong and diverse evals
kaggle.com
Use and download benchmarks for your machine learning projects.
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Getting a bunch of 429 rate limit errors with a quota exceeded message from @OpenAI's API, in spite of being well under quota and published rate limits
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NLC: natural language cron
We're excited to introduce Tasks! For the first time, ChatGPT can manage tasks asynchronously on your behalf—whether it's a one-time request or an ongoing routine. Here are my favorite use cases: 1/ ChatGPT checks stock price every morning!
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Just had the most obnoxious interaction I’ve had in a long time Jogging in quiet Palo Alto neighborhood. Middle-aged man and woman block away walking towards me Half a block away they start screaming “RUN ON THE FUCKING STREET SIDEWALKS ARE FOR WALKING NOT RUNNING. GET OFF THE
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Marimo's a delight to use for both exploratory Python notebooks and rapidly prototpying reactive data applications with a rich UI. It's replaced Jupyter notebooks for me. Excited to see what Akshay and team build from here!
My co-founder @themylesfiles and I have started Marimo Inc. to keep building the @marimo_io notebook and other Python data tools. We've raised a $5M seed round led by @antgoldbloom and @shyammani_ at @aixventureshq. Excited for the journey ahead! https://t.co/3TEJyKcBHU
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Looking at job posts over the last year, it looks like Amazon is making the broadest AI investment. 228 teams across the company posted jobs with GenAI projects over the past year, considerably more than any other company. https://t.co/z2mhUikaFH Most interest is the breadth of
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Fast hack to improve the factual accuracy of your LLM calls? Multi-LLM and consensus (e.g. majority voting) across them among the leading foundation models
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The overlooked GenAI use case: cleaning, processing, and analyzing data. https://t.co/klQjXiyODl Job post data tell us what companies plan to do with GenAI. The most common use case is data analytics projects. Examples: - AstraZeneca: using LLMs on freeform documents to
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10 data quality challenges in relational tables: 1. Duplicates 2. 3. Duplicates 4. Cḧarαctěr Énçødïng 5. 1/1/24 (ambiguous dates) 6. 7am (ambiguous times w/o timezones) 7. John A. Smith, john smith (fuzzy joining) 8. asdfasdfa junk record 9. Company: Apple Url:
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Close to 100% of machine code is now compiler-written. Higher levels of abstraction are how we move forward, faster
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I was born into the first computer-native generation My 2yo son’s in the first AI-native generation
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Admin consoles have their own circle of UX hell. If you can read this Google GSuite admin setting and tell me the difference between "Trusted" and "Limited", your English understanding is much better than mine
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For all the marketers that want to slap AI on a product name: as soon as I see "AI" in a product, I assume it's not going to work as advertised
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