I have fond memories of playing the original Falcon on my Amiga 500. It felt like magic after years of playing F15 Strike Eagle on the Apple IIc. Hearing real sound effects kicking in the afterburner and getting too close to the ground ("Pull Up! Pull Up!") were all so satisfying.
I remember being so excited when Falcon 3.0 came out. But it just felt like a let down. The graphics were amazing for the time and it seemed so realistic, but for me the realism is what killed all the fun. As a kid, I didn't actually want to BE an expert F16 pilot. I just wanted to feel like I was. I didn't want to have to learn all the systems and controls.
This article isn’t particularly helpful. It focuses on a ton of specific OpenAI business decisions that aren’t necessarily generalizable to the rest of the industry. OpenAI itself might be out over its skis, but what I’m asking about is the meta-accusation that AI in general is heavily subsidized. When the music stops, what does the price of AI look like? The going rate for chat bots like ChatGPT is $20/month. Does that go to $40 a month? $400? $4,000?
I keep seeing this charge that AI companies have an “Uber problem” meaning the business is heavily subsidized by VC. Is there any analysis that has been done that explains how this breaks down (training vs inference and what current pricing is)? At least with Uber you had a cab fare as a benchmark. But what should, for example, ChatGPT actually cost me per month without the VC subsidy? How far off are we?
Exactly. If you are an L7 and making an average L7 salary, nobody should have to squint and tie themselves in knots to figure out the connection between your contribution and your employer’s revenue. You are a Ferrari that is purchased new each year.
There’s a place where you can work on things that don’t generate revenue but are morally/technically interesting: it’s called “academia”.
Bingo. I wish I could upvote this comment more. All the geeks get distracted by words like “cloud” or “virtual” and forget that all this stuff we depend on has a physical presence at some point in the real world. That physical presence necessitates humans interacting with other humans. Humans interacting with humans falls squarely in the “things governments poke their noses into” bucket. It’s like the early days of Napster when people were all hot for “peer to peer”, as if that tech was some magic that was going to make record labels and governments throw up their hands over copyrights.
I highly recommend the piece by Derek Lowe down thread, but the tldr is basically that researchers have believed amyloid plaques cause the symptoms of Alzheimer's and so the theory is that if you eliminate them, you can treat the disease. This drug gets rid of them. But the gold standard is whether or not the drug actually helps people, not whether it meets a technical definition of "working".
This is the drug equivalent of an engineer following a requirements document and saying to a product manager, "Hey, you said the form has to be submitted through the website. You can see here when I hit submit, it submits! The website doesn't save the data anywhere because that wasn't in the requirements".
I was on one of the teams that refuted the claims of horizontal gene transfer in the original human genome paper. The bar for establishing a true case of horizontal transfer in vertebrates is high. It’s really improbable given the required sequence of events laid out in the article. It’s one thing for some DNA to get picked up by random cells in the organism (happens with viral infection all the time). Getting to the germline cells and becoming inherited is a whole other story given that vertebrates have evolved mechanisms to guard against this specific scenario.
In business, many times the lack of any decision (good or bad) wastes valuable time. Especially for leaders, unblocking teams to move forward has real value beyond whether or not the actual decision is optimal. A great many decisions are reversible. If your decision is reversible (even at some expense), it may be better to just decide and move on. In many cases, you don't have perfect information anyway, so trying to make the right decision causes you to delay the very experiments necessary to get you to an optimum outcome.
It’s not a vaccine if you don’t have efficacy data. You can go snort all kinds of peptides all day long, that doesn’t mean you’re going to actually have something useful happen.
Do you know why we’ve developed all these complex rules about how to test whether drugs and vaccines work? It’s because humans have reliably demonstrated over and over that we have no friggin’ clue how our bodies actually work. I worked in drug discovery. The one thing that all failed drug candidates had in common was that they all looked like surefire bets right up until the point where the data came rolling in. The reason all these complex studies and checks and balances are in place is because ~200 years of human experience making vaccines and medicine has given us some small amount of humility.
My daughter now 10 was diagnosed with a severe egg allergy around the time she turned 1. We aren't vegans and I love all kinds of things with egg (including home made pasta).
We tried so many egg replacers and were just not that impressed. I was resigned to giving up a whole bunch of foods I love. Aquafaba finally let us have so many normal meals back. You don't realize how many foods have egg in them (especially in restaurants: Orange Julius I'm looking at you! Who puts egg in fruit smoothies?!).
We use it to make pancakes, waffles, cakes, and even brownies (we found most egg replacers to be an utter disaster with many brownie recipes).
I would argue what makes the world a better place is ensuring companies have to innovate on their own. That’s what leads to breakthroughs and new things. Constraints often breed innovation. What is the incentive to sink billions into R&D if someone can sit on the sidelines and just take what you have developed? Look at the situation right now: we have multiple vaccine candidates from multiple companies because they all had significant incentive to develop them not because they were necessarily going to make a lot of money off this particular vaccine, but because they could accelerate R&D on tech they can use for other therapies. Some of these vaccine candidates appear to be mediocre at best. If we didn’t have a competitive marketplace we wouldn’t have gotten the best vaccine possible in the shortest timeframe possible.
There is sometimes specific information about the actual manufacturing process or synthesis that companies provide. Given that this is an entirely new vaccine technology that has never been used before, there was probably quite a bit of confidential manufacturing content supplied as supplemental material to satisfy regulators.
You are correct that the regulators are generally concerned with safety and efficacy of the final product, not the sausage making. But if the sausage making is super complex and/or novel that could potentially have an impact on safety and efficacy. So the company may have been asked to give some amount of detail there. For example: given this vaccine requires cold temperatures or it breaks down, how are they guaranteeing the cold chain in the manufacturing process? (I'm just using this as an illustration of the flavor of question someone on the committee might have)
Given how new this vaccine tech is, there are probably quite a few manufacturing-related efficiencies and techniques that Pfizer does not want competitors getting access to. Not because they're going to copy this specific vaccine, but because it allows them accelerate efforts in this area for other vaccines.
Syapse here! We are a real-world data company working across life science (pharma), hospitals, and with the FDA. We want to use real-world evidence to improve the outcomes of cancer patients. When many think of Health IT, they think primarily of patient tools, which are important. However, lots of decisions are made between pharma, hospitals, regulators and health plans that effect us; and aren't always grounded in what happens in the "real-world". We are hoping to help those decision-makers make better decisions for oncology patients using data, analytics and expertise.
It didn't come across in my post in retrospect, but just want to say clearly I love this idea and the ambitious nature of it. I think when someone works in drug discovery, it's hard to escape this feeling that there has to be a better, faster, cheaper way. But at the same time, the reality of seeing how little we actually understand about biological systems on display each and every day tends to be quite a downer! The world sorely needs more of this kind of thinking.
A few random thoughts I'm curious about (full disclosure: I worked in anti-infectives R&D as a bioinformatician early in my career for a major pharma)
1) One big challenge in synthesis is ensuring compound purity. Even when I was working in pharma, it was often the case that some of the compounds in the screening library could be contaminated with intermediates. This is murder for any kind of anti-infectives research because you end up with false-positives for toxic intermediates. Since your assay is often, "does the compound kill the bug?" the answer for most chemicals is, "yes!". How do you ensure the purity of what you deliver to your customers? If I'm a medicinal chemist wanting to try this, I want to know that I'm not getting a vial of brick dust back.
2) Just because you have a mechanism to synthesize, doesn't mean the yield is going to be great. Does your algorithm factor in yield when selecting the route?
3) When I started reading your post I thought, "Hats off to these folks, this is a super hard problem that no shortage of extremely smart people have spent years trying to solve." Then I got to the moonshot section! The number of small molecule antiviral drugs with efficacy is vanishingly small. I understand why you would try to tackle this, but it truly is a moonshot.
I remember being so excited when Falcon 3.0 came out. But it just felt like a let down. The graphics were amazing for the time and it seemed so realistic, but for me the realism is what killed all the fun. As a kid, I didn't actually want to BE an expert F16 pilot. I just wanted to feel like I was. I didn't want to have to learn all the systems and controls.