Thursday, 30th January 2025
Llama 4 is making great progress in training. Llama 4 mini is done with pre-training and our reasoning models and larger model are looking good too. Our goal with Llama 3 was to make open source competitive with closed models, and our goal for Llama 4 is to lead. Llama 4 will be natively multimodal -- it's an omni-model -- and it will have agentic capabilities, so it's going to be novel and it's going to unlock a lot of new use cases.
— Mark Zuckerberg, on Meta's quarterly earnings report
104. Technology offers remarkable tools to oversee and develop the world's resources. However, in some cases, humanity is increasingly ceding control of these resources to machines. Within some circles of scientists and futurists, there is optimism about the potential of artificial general intelligence (AGI), a hypothetical form of AI that would match or surpass human intelligence and bring about unimaginable advancements. Some even speculate that AGI could achieve superhuman capabilities. At the same time, as society drifts away from a connection with the transcendent, some are tempted to turn to AI in search of meaning or fulfillment---longings that can only be truly satisfied in communion with God. [194]
105. However, the presumption of substituting God for an artifact of human making is idolatry, a practice Scripture explicitly warns against (e.g., Ex. 20:4; 32:1-5; 34:17). Moreover, AI may prove even more seductive than traditional idols for, unlike idols that "have mouths but do not speak; eyes, but do not see; ears, but do not hear" (Ps. 115:5-6), AI can "speak," or at least gives the illusion of doing so (cf. Rev. 13:15). Yet, it is vital to remember that AI is but a pale reflection of humanity---it is crafted by human minds, trained on human-generated material, responsive to human input, and sustained through human labor. AI cannot possess many of the capabilities specific to human life, and it is also fallible. By turning to AI as a perceived "Other" greater than itself, with which to share existence and responsibilities, humanity risks creating a substitute for God. However, it is not AI that is ultimately deified and worshipped, but humanity itself---which, in this way, becomes enslaved to its own work. [195]
— Antiqua et Nova, Vatican Dicasteries
Mistral Small 3 (via) First model release of 2025 for French AI lab Mistral, who describe Mistral Small 3 as "a latency-optimized 24B-parameter model released under the Apache 2.0 license."
More notably, they claim the following:
Mistral Small 3 is competitive with larger models such as Llama 3.3 70B or Qwen 32B, and is an excellent open replacement for opaque proprietary models like GPT4o-mini. Mistral Small 3 is on par with Llama 3.3 70B instruct, while being more than 3x faster on the same hardware.
Llama 3.3 70B and Qwen 32B are two of my favourite models to run on my laptop - that ~20GB size turns out to be a great trade-off between memory usage and model utility. It's exciting to see a new entrant into that weight class.
The license is important: previous Mistral Small models used their Mistral Research License, which prohibited commercial deployments unless you negotiate a commercial license with them. They appear to be moving away from that, at least for their core models:
We’re renewing our commitment to using Apache 2.0 license for our general purpose models, as we progressively move away from MRL-licensed models. As with Mistral Small 3, model weights will be available to download and deploy locally, and free to modify and use in any capacity. […] Enterprises and developers that need specialized capabilities (increased speed and context, domain specific knowledge, task-specific models like code completion) can count on additional commercial models complementing what we contribute to the community.
Despite being called Mistral Small 3, this appears to be the fourth release of a model under that label. The Mistral API calls this one mistral-small-2501 - previous model IDs were mistral-small-2312, mistral-small-2402 and mistral-small-2409.
I've updated the llm-mistral plugin for talking directly to Mistral's La Plateforme API:
llm install -U llm-mistral
llm keys set mistral
# Paste key here
llm -m mistral/mistral-small-latest "tell me a joke about a badger and a puffin"
Sure, here's a light-hearted joke for you:
Why did the badger bring a puffin to the party?
Because he heard puffins make great party 'Puffins'!
(That's a play on the word "puffins" and the phrase "party people.")
API pricing is $0.10/million tokens of input, $0.30/million tokens of output - half the price of the previous Mistral Small API model ($0.20/$0.60). for comparison, GPT-4o mini is $0.15/$0.60.
Mistral also ensured that the new model was available on Ollama in time for their release announcement.
You can pull the model like this (fetching 14GB):
ollama run mistral-small:24b
The llm-ollama plugin will then let you prompt it like so:
llm install llm-ollama
llm -m mistral-small:24b "say hi"
PyPI now supports project archival. Neat new PyPI feature, similar to GitHub's archiving repositories feature. You can now mark a PyPI project as "archived", making it clear that no new releases are planned (though you can switch back out of that mode later if you need to).
I like the sound of these future plans around this topic:
Project archival is the first step in a larger project, aimed at improving the lifecycle of projects on PyPI. That project includes evaluating additional project statuses (things like "deprecated" and "unmaintained"), as well as changes to PyPI's public APIs that will enable clients to retrieve and act on project status information. You can track our progress on these fronts by following along with warehouse#16844!
Eventually, however, HudZah wore Claude down. He filled his Project with the e-mail conversations he’d been having with fusor hobbyists, parts lists for things he’d bought off Amazon, spreadsheets, sections of books and diagrams. HudZah also changed his questions to Claude from general ones to more specific ones. This flood of information and better probing seemed to convince Claude that HudZah did know what he was doing, and the AI began to give him detailed guidance on how to build a nuclear fusor and how not to die while doing it.
Datasette Public Office Hours 31st Jan at 2pm Pacific. We're running another Datasette Public Office Hours session on Friday 31st January at 2pm Pacific (more timezones here). We'll be featuring demos from the community again - take a look at the videos of the six demos from our last session for an idea of what to expect.
If you have something you would like to show, please drop us a line! We still have room for a few more demos.