AI – dr.Pep

Only preciously few companies have achieved the holy grail of continual learning… yet

Chip Huyen – Designing Machine Learning Systems

The book touches upon a refreshingly broad range of relatable challenges that are illustrated with practical examples.

We are not just living in a simulation: our brain is running the simulation and emotions are its predictions

Lisa Feldman Barrett – How emotions are made

Nice and usefull re-interpretation of what emaotions are, but I the anthropocentric way in which it contrasts emotions of humans and animals read as ‘goal seek’ that under-estimates the animal brain’.

There are so many guises in which intelligence manifests itself that it truly blows the mind

James Bridle – Ways of being

Enjoyable expansive thinking, unafraid of the pathetic.

AI will not take our jobs, but creep into our workflows and contribute as intern, coach, and idiot savant

Ethan Mollick – Cointelligence

Not wrong, but misses true depth and is overly-reliant on the author’s conversations with Chat-GPT.

To contain AI (and synthetic biology), humanity should bet on regulation

Mustafa Suleyman – The coming wave

In the light of the message of the book, the writer’s move to join Microsoft as AI chief in early 2024 was surprising.

Waking up

DeepDreamGenerator: “Journalist sitting at a desk at the newspaper office. The journalist grabs their own writings and trying to protect them, while fighting off a large crawler that wants to feed it to an AI.¨

Great to see journalists initiating change in their own organization.

Fri Aug 25: Guardian journalist Ariel B. reports that other news media have started blocking GPTbot. The subtly note in his article: “The Guardian’s robot.txt file does not disallow GPTBot.” (Version Sept 3, 2023)
Fri Sept 1: Guardian leadership has taken notice and blocks GPTbot – as reported here.

As I have noted earlier, data access is a major topic when it comes to achieving a healthy power balance in the information space here and here. Glad to see more and more companies take this seriously.

Personally, I currently see little incentives for companies, organization, or individuals to allow their data to be crawled by for profit.

There are a huge number of ways in which Artificial General Intelligence (AGI) can take over the world, rendering humanity essentially useless

Max Tegmark – Life 3.0

Nov. 2017: Interesting exploration of the implications of AGI, faulted by the typical preference of Analytical Philosophy for construction of intricate, highly theoretical scenario’s, under-emphasizing basic challenges (in the case of AGI: lack of robustness / antifragility).

Jun. 2023: The writer has leveraged the recent rise of LLMs like ChatGPT to further fuel fear about an AGI break-out – even though other AI-related risks require more imminent attention.

Determining the value function is a difficult problem that is nonetheless key to safely and effectively using reinforcement learning

Brian Christian – The Alignment Problem

The analogies between human and machine learning strategies are skillfully narrated, but rather drawn out.

Bayesian nets help prevent flawed statistical arguments and enable the leap from correlation to causation

Judea Pearl and Dana MacKenzie – The book of Why

The practical and relevant examples (health effect of smoking, impact of humanity on climate change) of causal inference alone make the book worthwhile.

AI increasingly constrains the domain of human creativity, similar to how science has constrained Faith

Marcus de Sautoy – The creativity code

Surprisingly up-beat considering its message and packed with nice examples.

Feigning intelligence is not too difficult, considering that people can be fooled in many different ways

Brian Christian – The most human human

Unfortunately, the book does not explicitly challenge if humans are adequate judges in the Turing test.

Turing’s suprisingly practical perspective on logic, intelligence, and machines was far ahead of his time

Andrew Hodges – Alan Turing: The imitation game

A quite complete account of the life and death of one of the most fascinating figures of early computing.

The US is losing out in AI, due to a lack of long-term vision and direction

Amy Webb – The big nine

The book’s set-up with multiple scenarios for the future works surprisingly well and is especiall concerning for European readers: Europe is almost completely irrelevant in all of Webb’s scenarios.

Economically speaking, AI makes prediction a commodity – and nothing more

Ajay Argawal, Joshua Gans, Avi Goldfarb – Prediction machines

The authors see AI as just a new option for the division of labor which, although it can have rather dramatic consequences, does not support apocalyptic GAI fearmongering.

AI outcomes reflect the thinking of the technochauvinists that built it – which may not be desirable for society

Meridith Broussard – Artificial Unintelligence

Great effort to democratize AI and peel off some layers of mistique that harm public debate (althought the case against technochauvinism seems at times a bit too shallow).