This was my memory of how Turbo was explained to me - keep it on if you want to go fast. We were all learning programming, so that's what we wanted - faster computers.
My observation is that right now AI coding agents lean towards re-implementing everything from the ground up. This of course will not scale. It will scale beyond what humans writing code would scale to, but we will ask the AI for more, so it will even things out.
1. We will develop new programming languages that are AI first, in that they are aimed at readability and comprehensibility by machines
2. We will adapt our working style (e.g. how we prompt and train the AIs) to factor in maintenance cost.
i.e. AI first implementations will go through the evolution we had with human based code development.
My observation is that right now AI coding agents lean towards re-implementing everything from the ground up. This of course will not scale. It will scale beyond what humans writing code would scale to, but we will ask the AI for more, so it will even things out.
Those who cannot do, preach.
There's a funny trick where if you are an experienced software developer, and take time to think about your design and describe what you want in clear terms, it will actually do things your way. Weirdly, this still saves massive amounts of time.
People who don't understand how to build good software LOVE to expound on the things we'll have to design in order to make AI tools "lean toward" building better software.
It seems that these folks are not willing or able to conceive of, you know, actually getting good at this stuff.
For this reason, it never occurs to them that human beings are STILL the source of the best ideas and designs.
Haven't heard of optogenetics in a while. I could never decide if it was actually useful for either basic science or medicine or a toy.
Looking at the basic science results I could not decide if they were bringing in really novel understanding or basically repeating a lot of the old electrical stimulation results.
I do remember a staggering amount of money was pumped into the field and it was super trendy in the 2010s.
Lets put it this way: prior to optogenetics, you had absolutely no way to answer questions like: "What happens during this behavior if we block dopamine at the exact moment we think dopamine is important for this behavior?" without trying our best to put a tiny electrode in the exact spot where we think dopamine neurons are found in the brain (on the micron scale), and pray that your stimulation exactly only hits dopamine neurons locally and nothing else (a technical impossibility).
now replace dopamine with any cell type you can think of in the brain, and you can even be more clever and do genetic tricks like "only this type of cell in this part of the brain that only receive input from this other part of the brain, but not others"
it really truly unlocked the entire era of neuroscience we are in, with the focus on circuits.
I predict the next likely era after circuits is networks, and the cool thing about opto is the scalability and the way we can precisely control and shape light to ultimately control networks.
Optogenetics is an incredible tool for probing and dissecting the activity of neurons within neural circuits. It’s gives enormous power to scientists to perform more causal manipulations and test ideas more concretely than observation or genetic manipulations alone. I’m not sure why it would be considered a toy, though the utility depends on what you do with it. So far this has been primarily limited to understanding the brain but there’s work to develop clinical therapies using optogenetics as well. I collaborated with Karl extensively in my PhD work with some others in the comments here. It’s exciting to see his work get this recognition.
it's a great tool for molecular elucidations. there's still a big gray area as to the interpretation of some results in the context of terms such as "memory" or various feelings, but the optogenetics framework is undoubtedly the most impressive interface to the brain ever created
There's a new strategy for treating loss of photoreceptors in the retina: reprogram fibroblasts with optogenetics to turn them into new photoreceptors. NEJM just had an article on this.
(This reminded me why I stopped reading magazines: they have low information density. They are more creative writing, journaling rather than terse and factual)
My take away on the answer to the headline question is:
Currently the lab grown meat is too expensive and not good tasting enough to compete with real meat and plant based alternatives exist so - not it’s time yet.
I moved to Fedora from Ubuntu about a year ago for my laptop. My main motivation was not be defaulted to snap packages. I have had a great experience i.e it gets out of the way and it doesn't fall apart when I update stuff. I was worried about SELinux but find Fedoras defaults just fine and intuitive.
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