27,375 karma · joined May 29, 2007
Writing https://digest.browsertech.com
Personal site: https://paulbutler.org
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> Prosecutors shall prioritize cases that hold accountable individuals who (a) cause financial harm to digital asset investors and consumers; and/or (b) use digital assets in furtherance of other criminal conduct, such as fentanyl trafficking, terrorism, cartels, organized crime, and human trafficking and smuggling. Seeking accountability from individuals who perpetrate these types of wrongdoing deters future illegal activity, compensates victims, and promotes the public’s confidence in the digital asset markets and broader industry. On the other hand, criminal matters premised on regulatory violations resulting from diffuse decisions made at lower levels of digital asset companies often fail to advance the priorities of the Department.
I read this as switching from proactive enforcement (stop the act before it causes damage) to reactive regulation (punish the guilty after the act happens). Proactive regulation of public markets makes sense because the general public has an interest in well-functioning capital markets even if they are not direct participants (markets are essentially the capitalist replacement for central planning).
It’s hard to make the same case for crypto, which (despite the insistences of its participants) more or less exists in isolation from the rest of the market. The industry feels it is over-regulated. Makes sense that a more lassiez-faire leader would take a more hands-off approach to it.
If you're talking about Rebecca Burke, it was almost three weeks. All for something that was at worst a naive understanding of the visa she needed.
https://www.independent.co.uk/travel/news-and-advice/rebecca...
This is true, but also generally true of any npm dependency that developers blindly trust.
The main difference with MCP is that it is pitched as a sort of extension mechanism (akin to browser extensions), but without the isolation/sandboxing that browser extensions have, and that even if you do run them in sandboxes there is a risk of prompt injection attacks.
Are you implying that Brian Krebs perpetuated suppression of legitimate dissent? Care to link it?
We've had tool call frameworks before, but we haven't had a way of making tools that our clients actually talked to. There was no way to build tools that other people could download and run locally without getting them to switch to a client that baked those tools in. It's like the difference between static linking and dynamic linking, but for tool calls.
Parker Conrad’s X thread is good: https://x.com/parkerconrad/status/1901615179718406276
Here’s the full complaint: https://rippling2.imgix.net/Complaint.pdf
We should be cautious about whether past precedent applies to future bitcoin, because the bitcoin halving mechanism ensures that bitcoin enters uncharted territory (with regards to the incentives at play) every four years for the next ~100.
Satoshi's design was that bitcoin would be used as cash and transaction volume would provide the funds to secure the network. That largely hasn't happened (it's a "store of value" now, lightning exists, etc.), so mining incentives are still ~95-98% funded from the exponentially diminishing supply of new coins.
Short of some institution stepping in to secure the bitcoin network by mining at a loss, it's hard not to imagine a 51% attack being relatively cheap on the time scale of decades.
- converted to png
- converted into a promise of an array buffer
- awaited
- converted into a Uint8Array
- passed to Deno.jupyter.image
Just to display it in the notebook. In Python Jupyter, you can just return many types and the library/Jupyter will figure out how to render them.
A few lines of code isn’t much but in my experience for interactive coding to be productive you have to remove every bit of friction and boilerplate you can.
This is meant to be usable for those use cases, but also to allow apps/agents to make API requests, load data from various sources, etc. It can also run in a company's cloud account, for compliance situations where they are running inference on their cloud account and want a ChatGPT-like code interpreter where data never leaves their VPC.
We give every repl its own network namespace and virtual ethernet device. We also apply a set of firewall rules to lock it out from making non-public-internet requests.
We've generally prioritized edge case handling based on patterns we see come up in LLM-generated code. A nice thing we've found is that LLM-generated code doesn't usually try to hold network connections or file handles across invocations of the code interpreter, so even though we don't (currently) handle those it tends not to matter. We haven't provided an official list of libraries yet because we are actively working on arbitrary pypi imports which will make our pre-selected list obsolete.
> Love what ForeverVM is doing and the early promise here.
Thank you! Always means a lot from someone who has built in the same area.