I don't think trans-disciplinary inquiry is arrogance - the intellectual fields are somewhat arbitrary relative to how human expertise relates to real world problems. But, effective trans-disciplinary inquiry requires awareness of philosophical commitments, and familiarity with existing literature/theory.
The bigger challenge might be that people with ML expertise need to solve problems of human-AI interaction and alignment because the training for the former is uni-disciplanary while the latter is trans-disciplinary.
Maybe an investment in "A-players" for streaming stifled cultural diversity and kept engineers from being able to innovate on novel media formats where they are losing engagement of the younger demographic to TikTok and other social media video formats.
The same corporate strategy and culture that hired "A-player" engineers for streaming is hiring "A-player" studios for content.
Defining A-players as such means you've set the rules of the game instead of building a culture of adaptive success criteria to meet customer opportunities. The label itself is a function of organizational ossification. This is the likely legacy of our tech giants; innovative in only one direction and not able to change fast enough to avoid becoming a brittle, mediocre institution over time.
As consumers, we can all feel this ossified mediocrity every day.
Agreed. The constraints of software engineering are mostly idiomatic. I used to use my "Scribe" mind to crawl through library dependencies for days to solve some artificial sub-problem.
No software engineer is good enough to time-efficiently write the whole stack from machine code up - it will always be an arbitrary and idiomatic set of problems and this is what LLMs are so good at parsing.
Using "Scribe" cycles to define the right problem and carefully review code outputs seems like the way.
The Enlightenment produced free speech and reasoning. Nietzsche said, "god is dead," but a lot of people said it before and after - because reasoning could not fill in the gap of a shared reality. Harari's Sapiens gives a good history; Hoffman's claim that "natural selection does not favor veridical perception" says you're pretty confused about what is actually going on wrt "truth"; Seth's "Being You" might help to understand what conscious beings are actually trying to do in relation "truth" and survival.
Some of the lower-hanging fruit in chemistry data was addressed by earlier versions of deep learning, like AlphaFold. It seems the nature of the domain is such that the language is less ambiguous than most natural language. Does anyone have a perspective on the apparent advantages of mapping chemistry interactions to latent space models for LLM training?
Omega-3 index is better correlated with overall health than O3/O6 ratio. Also, flaxseed is a source of ALAs whereas early all O3 health benefits come from DHA/EPA. A great source of info is Dr Rhonda Patrick's interviews w/ Dr Bill Harris. Here is a short clip - https://share.descript.com/view/2w6WidsYZlT
I think no one has posted the main thesis of this discussion. It's not just about "asking them", it's about the NYU psychologist's research that has systematically found no evidence for all counterfactuals other than asking a person about their internal state.
Knowing how to ask someone what they are thinking/feeling is a key skillset of anyone building a product for someone else. Its nuanced enough that books like "The Mom Test" break this down for entrepreneurs to implement tactically. On the other hand, West's research also suggests that one can comfortably underweight their own instincts laden with ego-centric and culture-centric biases. Further, you can also comfortably underweight the observations of your colleagues who might assert empathic abilities.
Perhaps the most interesting segment of this podcast was the story of how the author and her tenured colleague were able to dismiss their own intuitions about a acrimonious rivalry with one another and evaluate their relationship scientifically through hundreds of questions from their own research. They went from disliking one another to getting married.
See Labdoor.com and Consumerlab.com to verify supplement quality.
There are some good meta studies on Omega-3s. Dr Bradley Stanfield[1] walks through Mayo Clinic meta analysis[2]. Rhonda Patrick[3] is the best resource for an interpretation of the data.
TLDR; consume enough omega-3s (DHA/EPA) to get omega-3 index above 8.0. Discrepancies in research outcomes are attributed to study design, methodology of measuring intake, methodology of measuring blood.
Adopt the religion of biological age. ie, re-conceptualize your age as something that is correlated to your health, mortality and existential risk. Further its a number you have control to change. Exercising, eating healthier and learning more deeply about your body will give many options to feel better. The continued onslaught of scientific longevity advances will feel optimistic to your beliefs. Example: https://blueprint.bryanjohnson.co/
As another example, Amazon teams communicate product launch requirements via a future press releases including a FAQ (per description in the book "Working Backwards"). Its a communication intended for the masses with a built-in disambiguation addendum.
Our natural languages uses incremental inquiry to disambiguate context as opposed to using strong protocol. In "Working Backwards", it's the communicator's job to solicit questions from co-workers via pain-staking detailed reviews in meetings ("Bezos scrutinizes every single sentence"). I think of it like constructing a representative survey of ambiguity, and then putting answers in the FAQ that help increase clarity. The more detailed and representative your survey, the more helpful your questions/answers will be to communicate nuance.
With regard to disambiguating through protocol, Organizations evolve jargon to increment protocol, which probably increases semantic alignment somewhat as group size scales. If you read about the history of language, the Rebus principle created protocols of formal alphabets; protocols like grammar gave us formal writing rules. Protocols like TCPIP let our computers talk. Protocol creates more rigid commitments for communication, but also increases potential semantic alignment. As a thought experiment, if we learned to dynamically and deliberately develop jargons en masse, it might create the channels to disambiguate context and communicate nuance at scale.
Any thoughts on the organ-based biological age score that Bryan Johnson presents? More equivalent to monitoring all the components of the car.
I think these biological age scores are a really healthy way to debate and create broader awareness about a) how our bodies work and b) how we understand aging.
> The U.S North American Bird Conservation Initiative estimates that our pet felines kill some 2.6 billion birds annually in the U.S. alone.
The 100M pet cats in US on average kill 26 birds/yr? Doesn't seem right. When I track the source[1] of research, the estimates include both "own" and "unowned" cats and rely on some assumptions like "a correction factor to account for owned cats not returning all prey to owners", amongst others.
I was looking for something similar recently for a video clip and had a good experience with gifs.com. Their real-time preview was impressive, helpful. Any way you could offer that I can paste a youtube url instead of vid upload?
Paper is from 2016. Huberman Labs has a great roundup (Nov '21) of the research on time perception - and several other related series on dopamine. The title of OP was not surprising after listening. https://hubermanlab.com/time-perception-and-entrainment-by-d...
"Being You" by Anil Seth, released last month, is a great primer on predictive processing and its relationship to the science of consciousness. Its a great complement to Hawkins' latest. https://www.amazon.com/dp/B08W2J9WWD
The analysis of Cavalry and Iron is fascinating. As is the correlation between MilTech and Phylogeny (cultural similarity between polities).
I was most surprised that the authors had no strong theories about the role of "agricultural productivity". In addition to building armies from agricultural surplus, the ability to feed horses, people, elephants, etc was key to large military campaign. A common defensive technique against large army campaigns included burning agriculture.. for instance Hannibal's invasion of Rome. ie, the agriculture supply-chain itself seems to be a necessary pre-requisite to military campaigns with thousands of troops.