The Philosopher of Palo Alto

I just finished reading John Tinnell's The Philosopher of Palo Alto. Based on Stanford Library's extensive archive of Mark Weiser's papers, and interviews with many participants, it is an impressively detailed and, as far as I can tell, accurate account of the "ubiquitous computing" work he drove at Xerox PARC. I strongly recommend reading it. Tinnell covers Weiser's life story to his death at age 46 in 1999, the contrast between his work and that at Nick Negroponte's MIT Media Lab, and the ultimate failure of his vision.

Tinnell quotes Lucy Suchman's critique of Weiser's approach to innovation:

Under this approach, Suchman claimed, a lab "[provided] distance from practicalities that must eventually be faced" — but facing up to those practicalities was left up to staff in some other department.

To be fair, I would say the same criticism applied to much of the Media Labs work too.

As I was at the time a member of "staff in some other department" at Sun Microsystems and then Nvidia, below the fold I discuss some of the "practicalities" that should have been faced earlier rather than later or not at all.

2023 Storage Roundup

It is time for another roundup of news from the storage industry, so follow me below the fold.

Code Isn't Law: An Analogy

Source

In Trader Charged in $110 Million Market Scam Faces Dec. 4 Trial David Voreacos reports that Avraham Eisenberg is now in the "find out" phase:

Prosecutors claim Eisenberg manipulated Mango Markets futures contracts on Oct. 11, when he drove up the price of swaps by 1,300%. He used them to borrow about $110 million of cryptocurrency from other Mango depositors, the US alleges.

Four days later he posted on Twitter: “I was involved with a team that operated a highly profitable trading strategy last week.” He also said he believed “all of our actions were legal open market actions, using the protocol as designed.”

Below the fold, my analogy

A Local Large Language Model

I wanted to see what all the hype around Large Language Models (LLMs) amounted to, but the privacy terms in the EULA for Bard were completely unacceptable. So when I read Dylan Patel and Afzal Ahmad's We Have No Moat: And neither does OpenAI:

Open-source models are faster, more customizable, more private, and pound-for-pound more capable. They are doing things with $100 and 13B params that we struggle with at $10M and 540B. And they are doing so in weeks, not months.

I decided to try open source LLMs for myself, since as they run locally the privacy risk is mitigated. Below the fold I tell the story so far; I will update it as I make progress.

Flash Loans

I have been generally skeptical of claims that blockchain technology and cryptocurrencies are major innovations. Back in 2017 Arvind Narayanan and Jeremy Clark published Bitcoin's Academic Pedigree, showing that Satoshi Nakamoto assembled a set of previously published components in a novel way to create Bitcoin. Essentially the only innovation among the components was the Longest Chain Rule.

But, for good or ill, there is at least one genuinely innovative feature of the cryptocurrency ecosystem and in Flash loans, flash attacks, and the future of DeFi Aidan Saggers, Lukas Alemu and Irina Mnohoghitnei of the Bank of England provide an excellent overview of it. They:

analysed the Ethereum blockchain (using Alchemy’s archive node) and gathered every transaction which has utilised the ‘FlashLoan’ smart contract provided by DeFi protocol Aave V1 and V2. The Aave protocol, one of the largest DeFi liquidity providers, popularised flash loans and is often credited with their design. Using this data we were able to gather 60,000 unique transactions from Aave’s flash loan inception through to 2023

Below the fold I discuss their overview and some of the many innovative ways in which flash loans have been used.