Simon Willison’s Weblog

The memory shortage is causing a repricing of consumer electronics (via) David Oks provides the clearest explanation I've seen yet of why consumer products that use memory are likely to get significantly more expensive over the next few years.

The short version is that memory manufacturers - of which there are just three remaining large companies - have a fixed capacity in terms of how many wafers they can process at any one time. This fixed wafer capacity is then split between DDR - used in desktops and servers, LPDDR - used in mobile phones and low-energy devices, and HBM - used with GPUs.

Until recently, HBM got just 2% of that wafer allocation. The enormous growth in AI data centers has pushed that up to an expected 20% by the end of 2026, and "a single gigabyte of HBM consumes more than three times the wafer capacity that a gigabyte of DDR or LPDDR does".

Memory companies have learned from the extinction of their rivals that you should always under-provision rather than over-provision your fabricator capacity. The profit margins and demand for HBM (high-bandwidth memory) will constrain the production of consumer-device RAM for several years.

This is already being felt in the sub-$100 smartphone market, which is particularly important to markets like Africa and South Asia.

(The original title of the piece was "AI is killing the cheap smartphone" but I'm using the Hacker News rephrased title, which I think does more justice to the content.)

# 10:01 pm / memory, ai, ai-ethics

FTC to Require Cox Media Group, Two Other Firms to Pay Nearly $1 Million to Settle Charges They Deceived Customers About “Active Listening” AI-Powered Marketing Service (via) Back in 2024 Cox Media Group were caught trying to sell advertisers packages based on "active listening", with this deck which claimed:

• Smart devices capture real-time intent data by listening to our conversations
• Advertisers can pair this voice-data with behavioral data to target in-market consumers

I wrote about this in September 2024. My theory:

I think active listening is the term that the team came up with for “something that sounds fancy but really just means the way ad targeting platforms work already”. Then they got over-excited about the new metaphor and added that first couple of slides that talk about “voice data”, without really understanding how the tech works or what kind of a shitstorm that could kick off when people who DID understand technology started paying attention to their marketing.

This FTC press release appears to confirm that's pretty much what happened:

CMG, MindSift and 1010 Digital Works claimed their “Active Listening” branded marketing service listened in on consumers’ conversations overheard by smart devices, in real time, to target advertising [...]

According to the complaints, this service did not, in fact, listen in on consumers’ conversations or use voice data at all—nor did the service accurately place ads in customers’ desired locations. Instead, the service the companies provided consisted of reselling—at a significant markup—email lists obtained from other data brokers.

The FTC also clarify that hiding an "opt-in" to using voice data in terms of service would not be acceptable, as tricks like that do not constitute "adequate consent":

The FTC also alleged that all three companies deceived potential customers by claiming that consumers had opted into the Active Listening service. The company, however, did not seek or obtain consumers’ consent, according to the complaints. Instead, the companies claimed that consumers had “opted in” by agreeing to the terms of service that people have to accept when downloading and using apps. Clicking through mandatory terms of service does not constitute “opt-in consent” for such an invasive service or for use of consumers’ voice data from inside their homes. If the Active Listening service had functioned as advertised, this collection and use of consumers’ voice data without adequate consent would itself violate Section 5 of the FTC Act.

Attempting to myth bust the conspiracy theory that our mobile devices target ads to us based on spying through the microphones continues to be my least rewarding niche online hobby. It's nice to have a new piece of ammunition.

# 4:48 am / privacy, microphone-ads-conspiracy

How fast is 10 tokens per second really? (via) Neat little HTML app by Mike Veerman (source code here) which simulates LLM token output speeds from 5/second to 800/second.

Useful if you see a model advertised as "30 tokens/second" and want to get a feel for what that actually looks like.

# 5:57 pm / ai, generative-ai, llms

GDS weighs in on the NHS’s decision to retreat from Open Source. Terence Eden continues his coverage of the NHS' poorly considered decision to close down access to their open source repositories in response to vulnerabilities reported to them as part of Project Glasswing.

Now the Government Digital Service have joined the conversation with AI, open code and vulnerability risk in the public sector, published May 14th. Their key recommendation:

Keep open by default. Making everything private adds additional delivery and policy costs, and can reduce reuse and scrutiny. Openness should remain the default posture, with closure used sparingly and deliberately.

While they don't mention the NHS by name, Terence speaks the language of the civil service and interprets this as a major escalation:

Within the UK's Civil Service you occasionally hear the expression "being invited to a meeting without biscuits". It implies a rather frosty discussion without any of the polite niceties of a normal meeting. In general though, even when people have severe disagreements, it is rare for tempers to fray. It is even rarer for those internal disagreements to spill over into public.

# 3:59 pm / open-source, security, ai, generative-ai, llms, gov-uk, terence-eden, ai-ethics, ai-security-research

Welcome to the Datasette blog. We have a bunch of neat Datasette announcements in the pipeline so we decided it was time the project grew an official blog.

I built this using OpenAI Codex desktop, which turns out to have the Markdown session transcript export feature I've always wanted. Here's the session that built the blog. See also issue 179.

# 11:59 pm / ai, datasette, generative-ai, llms, ai-assisted-programming, codex