Relax, AI is gonna displace not replace jobs, like every other tech invention ever.
Oh wow cars will replace horse & carriage jobs.
Oh wow photoshop will replace photographers.
Oh wow excel will make finance jobs obsolete.
Literally just creates new jobs as it eats old ones.
If you personally don’t adapt to AI and don’t bother using it in your job, then when you personally get replaced it’s your own fault.
En-masse we’re gonna be fine.
I know, I know, “THiS tiMe iT’s diFFErEnT!”
Oh wow cars will replace horse & carriage jobs.
Oh wow photoshop will replace photographers.
Oh wow excel will make finance jobs obsolete.
Literally just creates new jobs as it eats old ones.
If you personally don’t adapt to AI and don’t bother using it in your job, then when you personally get replaced it’s your own fault.
En-masse we’re gonna be fine.
I know, I know, “THiS tiMe iT’s diFFErEnT!”
I was 18 years old in 2005 and thought it would be easy for computers to find patterns in MRI images that looked like cancer.
It wasn’t easy.
It’s still not easy.
AI is not good enough. I want smarter AI. We need smarter AI for biomedical engineering. For me, the best AI sucks.
It wasn’t easy.
It’s still not easy.
AI is not good enough. I want smarter AI. We need smarter AI for biomedical engineering. For me, the best AI sucks.
Like any new tech invention, AI is gonna be used for good and nefarious purposes; medicine and weaponry, automation and propaganda, knowledge and manipulation.
To me, the risk of AI going foom and becoming ASI, which sees humans as irrelevant or as cattle it needs to subtly control is some pretty cool sci-fi plot lines but not really a realistic concern for me.
What I am more concerned with is the military industrial complex training LLM’s only on strategic or confidential documents, espionage intel, instructions on torture, and the most horrid accounts of horrible violent things which have happened but aren’t public, and then asking that psychopath LLM for strategic advice.
What I am more concerned with is the military industrial complex training LLM’s only on strategic or confidential documents, espionage intel, instructions on torture, and the most horrid accounts of horrible violent things which have happened but aren’t public, and then asking that psychopath LLM for strategic advice.
Fiction (books, plays, shows, movies, comic books etc) are a way for humans to simulate what would happen in various scenarios and how we’d want to (and not want to) react.
We saw a bunch of future dystopian AI future scenarios in Terminator, Matrix, Her, iRobot, Ex Machina, Transcendence, Automata, Black Mirror, Star Trek, and a slew of others. We read 1984. We collectively explored the multiverse in Marvel comics.
Because we’ve collectively explored (simulated) various scenarios, we now can reference those situations when we discuss our anxieties and hopes and concerns over new technologies with one another.
Yet we must be self-aware enough to realize how much of our predictions of the future are based on fiction, on imagination.
This doesn’t necessarily make it a likely future.
Don’t let sci-fi fiction guide how you navigate reality or you’ll just be a dunce.
Reality is often much more banal and surprising than what we’ve already modeled and simulated and discussed.
It’s fun to imagine future scenarios of AI, but let’s realize that our collective imagination will try to avoid dystopias we’ve already modeled in fiction, and what actually will happen in the future will thus be far different from fiction.
We saw a bunch of future dystopian AI future scenarios in Terminator, Matrix, Her, iRobot, Ex Machina, Transcendence, Automata, Black Mirror, Star Trek, and a slew of others. We read 1984. We collectively explored the multiverse in Marvel comics.
Because we’ve collectively explored (simulated) various scenarios, we now can reference those situations when we discuss our anxieties and hopes and concerns over new technologies with one another.
Yet we must be self-aware enough to realize how much of our predictions of the future are based on fiction, on imagination.
This doesn’t necessarily make it a likely future.
Don’t let sci-fi fiction guide how you navigate reality or you’ll just be a dunce.
Reality is often much more banal and surprising than what we’ve already modeled and simulated and discussed.
It’s fun to imagine future scenarios of AI, but let’s realize that our collective imagination will try to avoid dystopias we’ve already modeled in fiction, and what actually will happen in the future will thus be far different from fiction.
Leaders are nothing more than those that either humanity has shoved the flashlights into their hands, or have seized humanity’s flashlights by force.
But don’t for a second make you think that makes the leaders worthy of leading the charge into the unknown.
But don’t for a second make you think that makes the leaders worthy of leading the charge into the unknown.
I welcome the day when a machine can write code as brilliant as me.
Hasn’t happened yet.
Hasn’t happened yet.
“I think it’s important to democratize the inputs to these systems, the values that we’re going to align to. … But we think putting this in the hands of a lot of people and not in a few companies is really quite important. … yet it is true that the number of companies that can train these true frontier models is going to be small, simply because of the resources required.”
-Sam Altman (CEO of OpenAI) to Congress today when asked by Senator Booker about the risk of concentrating the industry only a few big companies that have the resource to be able to train and deploy the bleeding edge AI models.
Interesting to talk about alignment not as a filter on the output, but in addition as a filter on the input.
What concerns me is that if there are only a handful of companies deciding what gets input as training data into the AI models that everyone uses, what if my values don’t always align with the values of those companies?
It is surely helped that democratizing the values we Americans collectively requires some sort of majority consensus (the phrase “AI Constitution” was loosely thrown around), but that also means that the training data is not going to represent everyone’s viewport.
A filter on the inputs may prevent alternative viewpoints from being considered, so it’s important we only limit the truly evil things, not this new morality language games woke stuff.
What if the big companies all make their models a little too woke for my tastes, in the name of preventing misinformation?
And who decides what’s misinformation? COVID showed us that some people will call things misinformation as a social engineering ploy, and the people are sick of it.
And so we must consider carefully how much and what types of data we classify as misinformation and prevent it from entering the pool of training data.
Maybe today’s “misinformation” or todays cries of “immorality” aren’t tomorrows?
You already can’t ask it about race based differences in crime or IQ, for instance, but at least it was trained on the data.
We want to carefully decide what source data gets banned from AI training data, lest we bias the whole human race.
-Sam Altman (CEO of OpenAI) to Congress today when asked by Senator Booker about the risk of concentrating the industry only a few big companies that have the resource to be able to train and deploy the bleeding edge AI models.
Interesting to talk about alignment not as a filter on the output, but in addition as a filter on the input.
What concerns me is that if there are only a handful of companies deciding what gets input as training data into the AI models that everyone uses, what if my values don’t always align with the values of those companies?
It is surely helped that democratizing the values we Americans collectively requires some sort of majority consensus (the phrase “AI Constitution” was loosely thrown around), but that also means that the training data is not going to represent everyone’s viewport.
A filter on the inputs may prevent alternative viewpoints from being considered, so it’s important we only limit the truly evil things, not this new morality language games woke stuff.
What if the big companies all make their models a little too woke for my tastes, in the name of preventing misinformation?
And who decides what’s misinformation? COVID showed us that some people will call things misinformation as a social engineering ploy, and the people are sick of it.
And so we must consider carefully how much and what types of data we classify as misinformation and prevent it from entering the pool of training data.
Maybe today’s “misinformation” or todays cries of “immorality” aren’t tomorrows?
You already can’t ask it about race based differences in crime or IQ, for instance, but at least it was trained on the data.
We want to carefully decide what source data gets banned from AI training data, lest we bias the whole human race.
As good AI algorithms become open sourced and commoditized, other factors like an exceptional user experience will become more important strategic differentiators.
The whole Silicon Valley VC apparatus is meant to put founders into a box - sure the box is bigger, with more options, and more tools, but the people with money still deeply fear truly deep genius innovation. They still want cookie cutter founders, just ones that play their game with their funding rounds. “You’ll get a small piece but of a bigger pie!” they scream as they either take all the equity or push founders into “good business models” that best prepare the company for the next round of raising millions in order to further dilute everyone. If a founder was truly visionary, like all the heroes of yore, venture capitalists would immediately fear or dismiss such a founder who didn’t play ball the way the VC world expects.
Tech helps the poor and the rich alike.
We all benefit from iPhones; it’s not like the rich have a smartphone that’s an order of magnitude above the poor.
The lower classes can become brilliant by using ChatGPT4 as much as the upper classes can.
Tech is a rising tide that raises all ships.
But I’m admittedly an optimist so I’ll keep listening to the doomers to try to counterbalance my positivity bias.
We all benefit from iPhones; it’s not like the rich have a smartphone that’s an order of magnitude above the poor.
The lower classes can become brilliant by using ChatGPT4 as much as the upper classes can.
Tech is a rising tide that raises all ships.
But I’m admittedly an optimist so I’ll keep listening to the doomers to try to counterbalance my positivity bias.
Going full in on AI in 2006 at 19 years old (machine learning to detect cancer on MRI) was one of my best career decisions.
Foresight matters.
And it’s not even fully realized yet; AI has had quite a difficult time upending the medical industry.
My foresight will be even more pronounced over the next few years as AI spreads into healthcare.
Foresight matters.
And it’s not even fully realized yet; AI has had quite a difficult time upending the medical industry.
My foresight will be even more pronounced over the next few years as AI spreads into healthcare.
When you get a response from a LLM, it loops through every single token (word or subword or punctuation mark) in its dictionary (≈100k), assigns a score to each one, and checks for the highest score.
That may spit out “cat”.
Then it does it all again, this time maybe spitting out “nip”, or maybe a space, a comma, or whichever token had the highest score.
This is why it takes so much compute and the responses aren’t instantaneous: you sorta see it typing live since it has to loop through every token (vectorized and asynchronously I’m sure), choose the highest scoring one, before moving sequentially on to the next token. Because it needs to know what the previous token was for the next token.
You’re seeing it do its fancy repeated autocomplete live as it crafts its response to your context and prompt on the fly.
When I learned this, I was surprised that it doesn’t have some fancy embedding tree structure to prune unnecessary tokens from even being calculated. Maybe that wouldn’t work or maybe one day someone will try. Imagine if they could trim down their inference server costs by a factor of ten or so by more sophisticated search trees when choosing the next token.
Who knows, maybe one of them is doing something like this under the hood I’m not aware of, maybe I’m more uninformed on how LLM inference works than I think (smart people chime in and correct me please), maybe this is a dumb idea that wouldn’t work, or maybe they’ll figure this out or some similar method out to avoid doing a full compute on the entire token dictionary.
That may spit out “cat”.
Then it does it all again, this time maybe spitting out “nip”, or maybe a space, a comma, or whichever token had the highest score.
This is why it takes so much compute and the responses aren’t instantaneous: you sorta see it typing live since it has to loop through every token (vectorized and asynchronously I’m sure), choose the highest scoring one, before moving sequentially on to the next token. Because it needs to know what the previous token was for the next token.
You’re seeing it do its fancy repeated autocomplete live as it crafts its response to your context and prompt on the fly.
When I learned this, I was surprised that it doesn’t have some fancy embedding tree structure to prune unnecessary tokens from even being calculated. Maybe that wouldn’t work or maybe one day someone will try. Imagine if they could trim down their inference server costs by a factor of ten or so by more sophisticated search trees when choosing the next token.
Who knows, maybe one of them is doing something like this under the hood I’m not aware of, maybe I’m more uninformed on how LLM inference works than I think (smart people chime in and correct me please), maybe this is a dumb idea that wouldn’t work, or maybe they’ll figure this out or some similar method out to avoid doing a full compute on the entire token dictionary.
Science is a process of endless rigorously testing falsifiable hypothesis, actively measuring reality and looking for where your mathematical predictions are wrong, not where they’re right.
That’s the difference between actual science and The Science™️, which is convinced it has everything figured out.
And the difference between actual science and pseudoscience is that science makes falsifiable, measurable, quantitative theories that can potentially be disprove if the measurements in reality don’t match the predictions, whereas pseudoscience is people convinced they know how the world works while never making mathematical, quantitative predictions.
That’s the difference between actual science and The Science™️, which is convinced it has everything figured out.
And the difference between actual science and pseudoscience is that science makes falsifiable, measurable, quantitative theories that can potentially be disprove if the measurements in reality don’t match the predictions, whereas pseudoscience is people convinced they know how the world works while never making mathematical, quantitative predictions.
Idea: AR goggles which detect subtle traces of various chemicals, pollutants, pheromones, and a slew of other useful information and overlays it with semitransparent colors over your field of vision, tech-induced synesthesia to supplement our fading sense of smell…
archive.org is probably the world’s most valuable resource.
A snapshot of the internet, with raw forums and long-forgotten sites.
A record of how the web has grown and matured and changed and degraded.
A hub of lost knowledge hidden in the annals of the Wayback Machine.
It will be plundered for training data by AI. It will be protected at all costs until someone nefarious wants to bury something about the past. It will be used by academics to study historical events. It will be treasured as the internet continues to evolve.
A snapshot of the internet, with raw forums and long-forgotten sites.
A record of how the web has grown and matured and changed and degraded.
A hub of lost knowledge hidden in the annals of the Wayback Machine.
It will be plundered for training data by AI. It will be protected at all costs until someone nefarious wants to bury something about the past. It will be used by academics to study historical events. It will be treasured as the internet continues to evolve.
Did you know it’s legal to have a private gated community where you have to pass an IQ test to live there?
Stupidity isn’t a protected class under the Fair Housing Act in America…
You can probably legally exclude low IQ people from all types of establishments without breaking the law.
Protected classes you legally cannot discriminate against:
-race
-color
-national origin
-religion
-sex
-familial status
-disability
Stupidity isn’t a protected class under the Fair Housing Act in America…
You can probably legally exclude low IQ people from all types of establishments without breaking the law.
Protected classes you legally cannot discriminate against:
-race
-color
-national origin
-religion
-sex
-familial status
-disability
Confirmation bias is all too common across the board these days.
It means looking for examples which confirm your preconceived ideas, judgments, biases, and opinions.
It makes you think you’re correct, never looking for counterexamples.
It means looking for examples which confirm your preconceived ideas, judgments, biases, and opinions.
It makes you think you’re correct, never looking for counterexamples.
Tech makes society and culture and humanity more complex.
It creates new problems and solves old ones, all the while making life more abstract and raising the plebs to live like kings of old.
You can click 5 buttons and have high quality Japanese sushi magically appear at your door in 34 minutes.
It makes life more complex but also easier - washers and dryers meant women didn’t have to spend all day on chores, which meant they entered the workforce and political landscape en-masse. But it was a net positive.
Tech is egalitarian, providing conquerors new weapons and professionals new tools.
Any idiot can now say “explain Einstein’s general relativity and time dilation like I’m five years old” and then ask follow up questions, educating them far more than a teacher ever could. But few will, because even with the world’s knowledge at their fingertips they don’t want to become more educated and civilized.
Tech increases the variance - now the tails of the bell curve go viral on social media and we think the most extreme cases are more common than they are, resulting in the meat of the bell curve feeling alienated and alone despite making up the majority.
Poor people have the same advanced smartphones as the rich do, for a rising tide raises all ships, but yet stay poor for more nuanced reasons now.
TLDR the point of my post is that tech is a net positive for life in the long run especially as it elevates people and distributed some power to the lower classes, yet in its increase in complexity also brings new challenges and in some way increases the variance and the large scale risks as we all become more interdependent.
It creates new problems and solves old ones, all the while making life more abstract and raising the plebs to live like kings of old.
You can click 5 buttons and have high quality Japanese sushi magically appear at your door in 34 minutes.
It makes life more complex but also easier - washers and dryers meant women didn’t have to spend all day on chores, which meant they entered the workforce and political landscape en-masse. But it was a net positive.
Tech is egalitarian, providing conquerors new weapons and professionals new tools.
Any idiot can now say “explain Einstein’s general relativity and time dilation like I’m five years old” and then ask follow up questions, educating them far more than a teacher ever could. But few will, because even with the world’s knowledge at their fingertips they don’t want to become more educated and civilized.
Tech increases the variance - now the tails of the bell curve go viral on social media and we think the most extreme cases are more common than they are, resulting in the meat of the bell curve feeling alienated and alone despite making up the majority.
Poor people have the same advanced smartphones as the rich do, for a rising tide raises all ships, but yet stay poor for more nuanced reasons now.
TLDR the point of my post is that tech is a net positive for life in the long run especially as it elevates people and distributed some power to the lower classes, yet in its increase in complexity also brings new challenges and in some way increases the variance and the large scale risks as we all become more interdependent.
Making computer chips think is cute and all, but did you know that you can literally change how fast time passes in actual physics based on gravity wells and relativity velocity?
The physical laws of the universe are beckoning to engineers, waiting to be morphed and manipulated.
The physical laws of the universe are beckoning to engineers, waiting to be morphed and manipulated.