Not A Bug But A Feature

Source

Datafinnovation are out with more impressive research described in a blog post entitled Losing The Blacklisting Race and a paper entitled Enforcement Speeds In DeFi: Limits to a Race Against Time by Ben Charoenwong et al.

The blog post is more accessible, so that's what I will quote from. But for the details you need to read the paper. The blog post's TL;DR is:

First, we explore the empirical reality of OFAC’s blacklisting efforts. The results there are stark: nearly all addresses are completely empty by the time OFAC manages to blacklist them. This result is robust across time, attacker and type of attack. Second, we construct a simple model to explain why this outcome is inevitable with competent attackers. Evasion strategies which work in our model match those we find employed in the wild.

Below the fold, I start from Datafinnovation's work and explore its context.

2026 Optical Media Durability Update

Eight years ago I posted Optical Media Durability and discovered:

Surprisingly, I'm getting good data from CD-Rs more than 14 years old, and from DVD-Rs nearly 12 years old. Your mileage may vary.

Here are the subsequent annual updates:

• 2019
• 2020
• 2021
• 2022
• 2023
• 2024
• 2025

It is time once again for the mind-numbing process of feeding 45 disks through the readers to verify their checksums, and yet again this year every single MD5 was successfully verified. Below the fold, the details.

More On Robotaxis

Cybercab

Liam Denning reports on Tesla's quarterly results flop in Someone Call Tesla a Robotaxi, or SpaceX, Quick. He notes that:

The curated list of investor questions that gets teed up ahead of these affairs had indicated some brewing discomfort about the big issue: Tesla’s lack of progress on its long-promised mass rollout of robotaxis. Musk duly tried to finesse this by pointing out that the “constraint” is safety, with Tesla trying to scale as fast as possible “while trying to ensure that we do not harm anyone.”

It is good that Tesla is "trying to ensure that we do not harm anyone" but they need to try much harder. In last February's Tesla's Not-A-Robotaxi Service I quoted Fred Lambert:

By the company’s own numbers, its “Robotaxi” fleet crashes nearly 4 times more often than a normal driver, and every single one of those miles had a safety monitor who could hit the kill switch. That is not a rounding error or an early-program hiccup. It is a fundamental performance gap.

But I went on to point out that Lambert was making the wrong comparison:

However badly, Tesla is trying to operate a taxi service. So it is misleading to compare the crash rate with "normal drivers". The correct comparison is with taxi drivers. The New York Times reported that:

In a city where almost everyone has a story about zigzagging through traffic in a hair-raising, white-knuckled cab ride, a new traffic safety study may come as a surprise: It finds that taxis are pretty safe.

So are livery cars, according to the study, which is based on state motor vehicle records of accidents and injuries across the city. It concludes that taxi and livery-cab drivers have crash rates one-third lower than drivers of other vehicles.

A law firm has a persuasive list of reasons why this is so. So Tesla's "robotaxi" is actually 6 times less safe than a taxi.

In any rational jurisdiction, six times worse than the competition even with a safety driver would get the regulators to force Tesla back to the drawing board.

The New York Times article was the best I could find at the time but it was from 2006. We now have much better and more recent data. Follow me below the fold for one of the reasons why Tesla's numbers are bad, very probably even worse than six, and even some criticims of Waymo's numbers.