HN user
I wonder, how does distillation deal with unprobed spaces in the knowledge landscape? Is a distilled model worse in some niche area that was not probed? Presumably, this is why frontier labs dont distill their own models internally to release them to the public as a servicable frontier model.
I wonder how much of the sloppy feeling is created by the knowledge that its AI generated.
Sure, but if we continue that analogy it does mean that there will be no human contributions to frontier mathematics.
Accelerationists may argue that the eroding of proper attribution and proof verification by humans is a meaningless short term struggle of a dying field.
Mathematics seems to be entering an era where human + machine maximizes performance, much like chess in the 1990s. However, imagine a future where even talented mathematicians are nothing but noise in the machine (as is the case in chess now). A future where AI generates and verifies proofs without humans in the loop. Where the mathematics may be beyond human comprehension.
In that future, does it matter that early career mathematicians are inhibited by these developments? Perhaps not. Programming faces the same issue. As AI crawls up the competence ladder, does it matter that fewer people have opportunities to develop the skillset of a senior engineer? Perhaps not.
Perhaps P=NP. The new algorithms are handed down to us. We can apply them without fundamentally understanding why P=NP.
Accelerationists may argue that the eroding of proper attribution and proof verification by humans is a meaningless short term struggle of a dying field.
Mathematics seems to be entering an era where human + machine maximizes performance, much like chess in the 1990s. However, imagine a future where even talented mathematicians are nothing but noise in the machine (as is the case in chess now). A future where AI generates and verifies proofs without humans in the loop. Where the mathematics may be beyond human comprehension.
In that future, does it matter that early career mathematicians are inhibited by these developments? Perhaps not. Programming faces the same issue. As AI crawls up the competence ladder, does it matter that fewer people have opportunities to develop the skillset of a senior engineer? Perhaps not.
"Generative AI is art. It’s irredeemably shit art; end of conversation."
I think most people cannot destinguish between "genuine" creativity and an artificial almalgamation of training data and human provided context. For one, I do not know what already exsists. Some work created by AI may be an obvious rip off of the style of a particular artist, but I wouldnt know. To me it might look awesome and fresh.
I think many of the more human centric thinkers will be disappointed at how many people just wont care.
There is genuine value in a wisdom of the crowds assessment of future events that is only sharpened up by the requirement to put money on the line.
Regarding point 2: I think most people cannot destinguish between "genuine" creativity and artificial almalgamation of training data and human provided context. For one, I do not know what already exsists. Some work created by AI may be an obvious rip off of the style of a particular artist, but I wouldnt know. To me it might look awesome and fresh.
Furthermore, I think many of the more human centric thinkers will be disappointed at how many people just wont care.
AI tools are here to stay. They will start to creep into everything, everywhere, all the time. Either you recognize the moment at which it becomes a significant disadvantage not to use them (I agree that moment is not now), or get left behind.
If you take the ambitions of robotics and AI companies seriously then what they are trying to create is the equivalent of unleashing 100 million cloned copies of the smartest and most well adjusted people you know upon the economy at a fraction of the cost. If they succeed it would absolutely reduce jobs significantly. In fact, its a little hard to imagine how the average Joe would have any economic value at all.
How about "bleeding edge"
Couldn't Google just do it better though?
I'm a genetic engineer at a large pharma company. We corrected the HTT gene in patient derived iPSCs in the lab. The region is a long repeat sequence of which a section needs to be deleted. Because of this the locus is quite difficult to genetically engineer, since it is difficult to target just the diseased allele but not the wild-type allele.
Typical gene therapeutic approaches probably wont work, e.g. Cas9 (you'd need two cuts to delete the sequence), Base editors (cant delete sequence), prime editing (deletion is too large for standard prime editing).
You'd either need a template based system such as homologous recombination (too inefficient) or something like twin-prime editing, but good luck getting that to work on repeat sequence.
One would probably engineer these cells with a killswitch, such as doxycycline induced Caspase9 https://pmc.ncbi.nlm.nih.gov/articles/PMC1895037/.
The transgene engineering is totally possible without a viral vector. We engineer cells all the time with recombinase based editing methods for targeted safe harbor insertion of transgenes https://www.nature.com/articles/s41551-024-01227-1. This stuff just permeates through the community slowly.
Regarding point 3: The problem from the perspective of websites would not be any different if they had been completely ad free. People would still consume LLM generated summaries because they cut down clicks and eyeballing to present you information that directly pertains to the promt.
The whole concept of a "website" will simply become niche. How many zoomers still visit any but the most popular websites?
Let me clarify that I dont think any of what I described is a given. I think its one of the more likely outcomes of our future. I think its prudent to own a small amount of Bitcoin (or basket of cryptocurrencies) in order to hedge against that future or someting close to it.
What about the other thousands of other public blockchains, many of which are extremely similar (DOGE, BCH, LTC, ...)?
They are simply not as secure and could be attacked by well funded actors. Perhaps in time another blockchain will win out.
... Metaverse anytime now.
Just curious. Do we disagree about where this (technological progress) is headed, or is it the timeline? I think its quite likely that we will spend more and more time in vitual or augmented reality. For good or ill.
Personally, I think there is much more value in trusted systems.
I prefer the absence of a central authority. Perhaps im cynical.
... because the world didn't work at all prior to 2009?
We dont need crypto right now either. I simply think that the only good outcome of our digital future is a trustless one, and I think blockchain will play a central role there.
Solutions to this problem might well involve digital signatures and hardware enclaves in cameras (installed by trusted centralized camera producers which could publish the public keys of each sold camera once), but I don't see how public blockchains would add any value. The signature of the picture embedded in the picture speaks for itself.
The value of blockchain is in the absence of a trusted centralized camera producer that can be pressured.
Apart from the fact that I don't see the benefit of that, the oracle problem makes this impossible, I fear.
The oracle problem is solved in the same way the camera problem is solved. By digital signatures of real world interactions of the machines in the production chain.
I think the world will lean into trustless systems over trusted systems, lets see. That is not to say that I dont think the world would continue to function on trusted systems, I just think it makes dystopian outcomes more likely.
Bitcoin is the only immutable peer to peer system ever created (barring advances in quantum computing, and even then the protocol can be updated). In a world headed toward web 3.0, generative AI content & virtual reality, I think there is tremendous value in a trustless and immutable peer to peer system. In fact, I think we NEED it, and should as a society happily bear the power consumption that underpins the security of the network.
Controversial, I know. However, already we cannot trust that a digital picture is genuine. There is currently no solution to this problem. In the near future, I imagine that the raw data of your camera will be associated with a token on a blockchain (not bitcoin, but a dedicated high-capacity blockchain). Such a system would allow us to determine that a picture was indeed taken with a physical device, and thus that the events depicted have a bearing in the real world.
My bet is that we are headed toward a future where blockchain is ubiquitous. Where everything of value is underpinned by a specialized blockchain. When you order groceries, the origin of the produce and raw ingredients are all embedded in blockchain. In virtual reality, every digital product has a specialized blockchain. Every kind of transaction; compute, assets, AI, will all be underpinned by trustless peer to peer systems.
All these specialized blockchains trade security for throughput. My bet is that Bitcoin will act as a security guarantor in our future digital society, where the state of every blockchain is periodically validated on the Bitcoin network. Thus, I bet that every transaction in the future will have an associated Bitcoin cost. Thats why I own a small amount of Bitcoin.
Obviously, an LLM is in a perfect position to decide whether an add can be "injected" into the current conversation. If you're using it for creative writing it will be add free. But chances are you will also use it to solve real world problems where relevant adds can be injected via product or service suggestions.
I added my credentials to address the "malicious scientist" scenario that some people may associate with leaked genetic information. You dont need an individual's genome to create rather dangerous gentic weaponry.
For example, we now have cell-penetrating prime editor ribonucleoproteins, a derivation of the CRISPR system. These are essentially assembled molecular machines that can be loaded install almost any genetic mutation, such as tumor driver mutations. A picogram of this protein complex is potentially enough to riddle your body with cancer a couple of years after delivery.
The impact of lifestyle is undeniable and large. Good genes will not protect your body from alcoholism. And if I were a betting man, I would bet against determinism emerging from a better understanding of combinatorial genetics.
I do think over time we will get a clearer picture of risk predisposition based on your entire genetic profile. However, I believe that genetic predisposion will remain a relatively small contributor for most disease states.
For the vast majority of people lifestyle is much more deterministic than genetics. There are a few exceptions causing relatively deterministic adult onset diseases: Huntington, APOA4 homozygosity, FAP, BRACA mutants. These are rare however.
I'm a genetic engineer at a large pharma company. Genetic engineering of human model systems is my specialty. If I were a malicious actor, I could not do anything useful with the genome of any one person.
Most peoples genomes are boring and at best sway the predisposition for disease by a modest degree. Exposing infidelity is honestly the best I can come up with.
We are on the cusp of being able to plow through vast quantities of literature and data in an instant using multimodal machine learning models. Journal articles are written for people. The landscape is changing. We are headed toward a future where scientist upload data and thoughts en masse into the cloud to be consumed by interpreter models that in turn feed back into the scientific machine. Data quality and attribution (scientist performance rating) is automatically allocated by models.
We are on the cusp of being able to plow through vast quantities of literature and data in an instant using multimodal machine learning models. Journal articles are written for people. The landscape is changing. We are headed toward a future where scientist upload data and thoughts en masse into the cloud to be consumed by interpreter models that in turn feed back into the scientific machine. Data quality and attribution (scientist performance rating) is automatically allocated by models.
Take a look at Nick Bostrom's new book
Randomness just introduces branch points into the linear flow of deterministic states. Since you do not control the branch points or create them, this does not give you free will.
Its a bit much to ask for people, in the face of such exceptional wealth prospects, to stay steadfast in their initial commitment.
There is only so much that you can get out of tinkering with naturally evolved proteins. I suspect that these kind of tools can be used to generate smaller & brighter FP's in the near future.
Very nice work. We need brighter fluorescent protein tags that are more compact, in particular in the far red spectrum. The size of current fluorescent protein coding DNA sequences is out of reach of prime editing and still relies on less efficient gene editing technology.