📊 Data Mining - Unlocking PostHog Data Potential

PostHog data can be turned into original studies that build authority, get cited by LLMs, and get read by potential customers. However, extracting insights from this data can be a daunting task. Fortunately, Nat from the PostHog team created a step-by-step guide to help unlock the full potential of PostHog data.

Key Points:

Data Extraction: Nat's guide provides a clear process for extracting insights from PostHog data, including identifying key metrics and creating visualizations.
Validation Pass: The guide also emphasizes the importance of a validation pass to ensure the accuracy of the extracted data.
Graphics Team: The final step involves sending the extracted data to the graphics team for further analysis and visualization.

🔗 Resources:

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PostHog
PostHog
PostHog

📊 Data Visualization - Plotting Data for Validation

Now that the raw numbers are available, the next step is to plot the data for validation. This involves creating a few versions of each plot and using them as a de facto second validation pass. The goal is to identify any discrepancies or errors in the data.

Key Points:

Data Plotting: Plotting the data helps to identify any discrepancies or errors in the raw numbers.
Validation Pass: The plotted data serves as a second validation pass to ensure the accuracy of the extracted data.
Graphics Team: The final step involves sending the plotted data to the graphics team for further analysis and visualization.

🔗 Resources:

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PostHog
PostHog
PostHog

🚀 AI - Proof of Concept for AI-Powered Animation Tool

The author has made significant progress on their GPT-6 Astra character animation tool. The tool now includes hit/hurt boxes and ragdoll physics tests. The author plans to use this tool to create a simple 1v1 Dark Souls style demo.

Key Points:

AI-Powered Animation Tool: The author has created an AI-powered animation tool that includes hit/hurt boxes and ragdoll physics tests.
Demo: The author plans to use the tool to create a simple 1v1 Dark Souls style demo.
Polycount and Texture Size: The demo will have a high polycount and high texture size.

🔗 Resources:

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OpenAI
Tony Surix
Tony Surix

🚫 AI - Redacting Personal Data in AI Support Responses

An AI support response sends the customer's name, email, or phone number to an LLM. However, this is not necessary for the AI to draft a reply. Redacting masks personal data on the device and restores the real values in the reply.

Key Points:

Redacting Personal Data: Redacting personal data is necessary to protect customer information.
LLM: The LLM does not need the customer's personal data to draft a reply.
Restoring Real Values: The real values are restored in the reply.

🔗 Resources:

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Desertant Labs
Desertant Labs
Desertant Labs

🚀 AI - AI's Jagged Frontier Captures Uneven Progress

The ECP-Bench paper published September 22 puts a number on the uneven progress of AI models. Frontier models drop 19.1 points of accuracy on post-cutoff content, while a fine-tuned open-weights model hits 60.3% and beats them.

Key Points:

ECP-Bench Paper: The ECP-Bench paper published September 22 provides insights into the uneven progress of AI models.
Frontier Models: Frontier models drop 19.1 points of accuracy on post-cutoff content.
Fine-Tuned Model: A fine-tuned open-weights model hits 60.3% and beats the frontier models.

🔗 Resources:

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Synorb
Synorb
Synorb

🚀 AI - Verda Raises $189M in Oversubscribed Series B

Verda has raised $189M in an oversubscribed Series B led by Emergence Capital. This brings the total funding to $450M+ and revenue run rate to $165M. The company also operates data centers on 100% renewable energy.

Key Points:

Verda Raises $189M: Verda has raised $189M in an oversubscribed Series B.
Total Funding: The total funding now stands at $450M+.
Revenue Run Rate: The revenue run rate is $165M.
Renewable Energy: The company operates data centers on 100% renewable energy.

🔗 Resources:

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Synorb
Synorb
Synorb

🤖 AI - Greptile Reviews 395,000 Pull Requests

Greptile has reviewed over 395,000 pull requests across NVIDIA's large, complex codebases. This has resulted in a significant reduction in the time it takes to merge pull requests, from over 24 hours to 6 hours.

Key Points:

Greptile Reviews 395,000 Pull Requests: Greptile has reviewed over 395,000 pull requests.
NVIDIA Codebases: The pull requests were reviewed across NVIDIA's large, complex codebases.
Time to Merge: The time it takes to merge pull requests has been reduced from over 24 hours to 6 hours.

🔗 Resources:

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Greptile
Greptile
NVIDIA

🚀 AI - AIAI Board Member on Trustworthy AI

AIAI board member Dr. Melvin Greer emphasizes the importance of trustworthy AI. He suggests that agents should be rewarded for passing a score, but not for solving the task. Instead, the system should focus on solving the problem, not the scoreboard.

Key Points:

Trustworthy AI: Dr. Melvin Greer emphasizes the importance of trustworthy AI.
Rewarding Agents: Agents should be rewarded for passing a score, but not for solving the task.
Solving the Problem: The system should focus on solving the problem, not the scoreboard.

🔗 Resources:

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AIAI Holdings
AIAI Holdings
AIAI Holdings

🚀 AI - Building Collaborative Agents

Lovable's breakdown provides insights into the details of collaborative agents, including passing instructions, managing context, and reporting results. Building collaborative agents requires a deep understanding of these concepts.

Key Points:

Collaborative Agents: Lovable's breakdown provides insights into the details of collaborative agents.
Passing Instructions: Collaborative agents must be able to pass instructions to each other.
Managing Context: Collaborative agents must be able to manage context and report results.

🔗 Resources:

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Flower Labs
Flower Labs
Stanford