GENERATIVE AI

Reinforcement Learning Limitations on Fine-tuned Model Prompts

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31 March 2026 22h55

No, RL doesn't fix it. It merely makes e smaller for prompts present in the fine-tuning set.

LLMs and Code Generation Systems: Clarifying Autoregressive Architecture

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31 March 2026 22h53

1. I never said LLMs were not useful 2. Code generation systems are not strictly auto-regressive LLMs. They produce multiple outputs and pick the best ones. 3. Your argument is as if I said "perpetual motion is impossible" and you responded "meanwhile, it's been 300km since I

→ View original post on X — @scobleizer, 2026-03-31 20:52 UTC

Gemini Agent Mode: Powerful Alternative to OpenClaw for Automation

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@scobleizer

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31 March 2026 22h52

Friendly reminder that Gemini has a built-in alternative to OpenClaw. Yes.

Agent mode can literally perform any task:

– Leverage a web browser to use any site/tool
– Connected to Gmail, Calendar, Drive, Tasks, etc.
– Generate presentations with Slides
– Use YT videos as sources… pic.twitter.com/QllVIbPCaE
— Paul Couvert (@itsPaulAi) 31 mars 2026

Friendly reminder that Gemini has a built-in alternative to OpenClaw. Yes. Agent mode can literally perform any task: – Leverage a web browser to use any site/tool – Connected to Gmail, Calendar, Drive, Tasks, etc. – Generate presentations with Slides – Use YT videos as sources – Create tasks, archive emails, draft responses And much more like deep research, canvas and so on. You can also ask Gemini to run Agent every day, once a week, etc. for recurring tasks. Probably the feature that people sleep on the most.

→ View original post on X — @patio11

Impact of AI Transcription Tools on Labor Utilization

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@patio11

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31 March 2026 22h48

A data point: prior to AI tools being good enough to offload some of the work, my podcast transcripts were ~$250 of transcriptionist labor plus about 5 hours of work from yours truly. The first pass is now AI. So what's the impact on labor utilization for transcripts?

→ View original post on X — @patio11

Impact of AI tools on transcription labor workflows

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@patio11

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31 March 2026 22h48

As a single data point: prior to AI tools being good enough to offload some of the work, my podcast transcripts were ~$250 of transcriptionist-hours plus about 5 hours of work from yours truly. The first pass is now AI. So what's the impact on labor utilization for transcripts?

Clarifying the utility debate around large language models

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31 March 2026 22h41

I never said LLMs were not useful. We're discussing a different question here.

Error Recovery Impossibility in Autoregressive Models

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31 March 2026 22h39

You didn't understand either. Yes, the independence of errors is an assumption, which may or may not be reasonable. No, errors are NOT RECOVERABLE in an auto-regressive setting because the set of correct answers form a subtree in the tree of all possible sequences. Once you get

Autoregressive Prediction and Stochastic Generation in AI Models

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31 March 2026 22h34

No. Auto-regressive prediction produces a single path in the tree of possible sequences. At non-zero temperature (stochastic generation) the potential paths form a subtree of the full tree, or rather, a distribution over all paths in the tree. If you threshold all the paths

→ View original post on X — @databricks

Genie Code: Autonomous AI Partner for Data Analysis

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@databricks

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31 March 2026 22h21

[DEMO] Genie Code is your autonomous AI partner for data work.

Starting from a single prompt, watch as it explores datasets, trains and evaluates models, builds a Lakeflow Spark Declarative Pipeline, and creates an AI/BI dashboard – all while maintaining enterprise context.… pic.twitter.com/tgdNAgV8Ke
— Databricks (@databricks) 31 mars 2026

[DEMO] Genie Code is your autonomous AI partner for data work. Starting from a single prompt, watch as it explores datasets, trains and evaluates models, builds a Lakeflow Spark Declarative Pipeline, and creates an AI/BI dashboard – all while maintaining enterprise context.