A new term I’m hearing more often, “authentic data,” illustrates a concern among data buyers and users that machine-generated errors will lead them astray. https://www.dbreunig.com/2025/01/20/on-authentic-data.html
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Making your own evals is essential if you're building with LLMs.
Here's a quick example eval and a demo of its utility when choosing models, optimizing prompts, and more: https://www.dbreunig.com/2025/01/08/evaluating-llms-as-knowledge-banks.html
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Summed up best by @annaleen https://www.newscientist.com/article/mg26234952-100-what-everyone-gets-wrong-about-the-2015-ashley-madison-scandal/
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I tend to think the Ashley Madison leak, where it was revealed most of the “women” on it were bots is the most foreshadowing story of this era.
Networks will continue to hack our perception like orchids tricking pollinators, so long as PM’s keeping using engagement as their key metric.
https://nymag.com/intelligencer/article/meta-wants-more-ai-bots-on-facebook-and-instagram.html
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OpenAI is Netscape is a really interesting take. https://mastodon.social/@daringfireball/113738152855628766
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Really enjoy DSPy’s workflow for LLM work. Handing off the specifics of prompt generation and engineering back to the LLM makes a lot of sense: https://www.dbreunig.com/2024/12/12/pipelines-prompt-optimization-with-dspy.html
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I want a speaker that:
It is surprisingly difficult to find!
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Reviewing the history of machine learning, we can both understand how LLMs advanced so quickly and why they've hit a wall.
We used 3 decades of Internet data and graphics innovation all at once. It's slow going from here on out.
https://www.dbreunig.com/2024/12/05/why-llms-are-hitting-a-wall.html
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When You're Raising: "It is possible that we will have superintelligence in a few thousand days."
When You Want Out of a Profit-Sharing Contract w/ Microsoft: "My guess is we will hit AGI sooner than most people in the world think and it matter much less."
https://www.theverge.com/2024/12/4/24313130/sam-altman-openai-agi-lower-the-bar
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What a novel idea. https://www.theverge.com/2024/11/21/24302400/threads-algorithm-focus-people-you-follow
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It's a static site that's updated hourly with Github Actions. You can tweak the code to your heart's content. Here's the write up: https://www.dbreunig.com/2024/10/29/generating-descriptive-weather-forecasts-with-llms.html
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Here's a little LLM demo using a model to generate weather reports based off webcam images and current conditions: https://sfweather.dbreunig.com
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“My ‘I am Principled’ op-ed has a lot of people asking questions already answered by my op-ed.”
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Simplifying the AI noise by segmenting everything into 3 big use cases: Gods, Interns, and Cogs. https://www.dbreunig.com/2024/10/18/the-3-ai-use-cases-gods-interns-and-cogs.html
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Here's mine by the way, made probably 25 laters:
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Bonham's latest History of Science & Technology auction is up. The highlight for me is this Blue Box from 1972: https://www.bonhams.com/auction/29514/lot/31/blue-box-phone-hacking-device-blue-box-c-1972/
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$160 billion dollars invested.
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Joining Overture Places with county health restaurant grades using DuckDB, Ollama, and more. https://www.dbreunig.com/2024/09/27/conflating-overture-points-of-interests-with-duckdb-ollama-and-more.html
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What would an AI collapse leave behind? https://www.dbreunig.com/2024/09/23/what-remains-if-the-ai-bubble-bursts.html
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So…………what iOS podcast player do you all recommend?
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