121–130 of 167 posts
I was working at an Apple Store when Jobs died. People started to leave flowers, management put up huge sheets of paper in the windows and people wrote all sorts of heartfelt messages. What other CEO’s passing would engender that kind of sentiment? Those people didn’t just prefer Apple equipment, they loved it. Jobs tapped into something deep with his ethos and product vision. He had an uncanny knack of understanding…
With celebrities like Steve Jobs we have a lot of interviews, autobiographies and data available. It would be interesting to finetune a LLM using all this data to act like him. Then you add TTS with his voice and voilà: Your personal Steve Jobs personal advisor running on your GPGPU or even phone, eventually. Makes you wonder if there will be laws against doing this without permission eventually. It's kind of hard to…
Here is what Steve Jobs said about this in 1983 (copied from the book): "The problem was, you can’t ask Aristotle a question. And I think, as we look towards the next fifty to one hundred years, if we really can come up with these machines that can capture an underlying spirit, or an underlying set of principles, or an underlying way of looking at the world, then, when the next Aristotle comes around, maybe if he car…
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As Aristotle, I would like to reflect upon the relationship between Large Language Models and human knowledge and cognition.
Firstly, it is important to understand that knowledge and cognition are closely intertwined with language. Human beings have the unique ability to use language as a tool to convey and acquire knowledge. However, with the emergence of Large Language Models, such as GPT-3, we are now seeing machines that can also manipulate language to produce and process knowledge.
These machines are built using complex algorithms and trained on vast amounts of data, allowing them to produce outputs that can mimic human language to a remarkable degree. However, it is important to note that these models are not conscious beings, and their outputs are based solely on the patterns they have learned from the data they were trained on.
While Large Language Models can certainly augment human knowledge and cognition by providing access to vast amounts of information, they cannot replace the unique capabilities of the human mind. Human beings have the ability to reason, to form concepts and abstractions, and to apply knowledge in creative and innovative ways. These are capabilities that cannot be fully replicated by machines, at least not at present.
In conclusion, while Large Language Models can certainly contribute to human knowledge and cognition by providing access to vast amounts of information, they cannot replace the unique capabilities of the human mind. The human mind remains a unique and powerful tool, capable of processing and synthesizing knowledge in ways that machines are not yet able to replicate.
Earlier quoted context omitted.
> Assembling top talent is something a lot of people could do Absolutely not. First you need the ability to recognize top talent. That's already super hard. Then you have to convince them to come work for you. Top talent is not always just motivated by money alone, so how do you attract them? Then after you hire them you have to retain them, which is also hard, because you have to understand what they are building, a…
It's one of the hardest things any leader will ever have to do. Jobs said as much repeatedly. Older Jobs lavished credit onto his teams because he knew very well how hard it is to put them together and keep them together. And if you can manage to acquire them, and if you can manage to retain them, you have to then manage them as an individual and in function with a lot of other people that will inevitably clash at ti…
He sure knew how to keep people together!
https://www.theguardian.com/technology/2014/jul/08/steve-woz...
It's amazing how much "mystique" is assigned to a man who's success can probably be at least 75% attributed to just being an enthusiast about his own products in a business world where it's usually limited to the founding members. How many CEOs, product managers and the like have been caught promoting their own brand with a "tweeted from iPhone" tagline. Probably "efficient business people", but literally won't touch…
It is surprising how hard it is to find co-founders with business experience who will actually be enthusiastic about the product they are supposed to promote. I am a technical founder who has tried (and failed) a few times to get a business partner on board to promote and sell the product. I had two guys join on with big talk about how they were perfect for turning it into a home-run project. Neither one lasted even…
What did Steve Jobs actually make other than hype? He wasn't an engineer and wasn't an inventor. He was a salesman (a great one!) but a salesman at the end of the day.
"The problem was, you can’t ask Aristotle a question. And I think, as we look towards the next fifty to one hundred years, if we really can come up with these machines that can capture an underlying spirit, or an underlying set of principles, or an underlying way of looking at the world, then, when the next Aristotle comes around, maybe if he carries around one of these machines with him his whole life—his or her whole life—and types in all this stuff, then maybe someday, after this person’s dead and gone, we can ask this machine, “Hey, what would Aristotle have said? What about this?” And maybe we won’t get the right answer, but maybe we will. And that’s really exciting to me. And that’s one of the reasons I’m doing what I’m doing."
Earlier quoted context omitted.
I've worked hand-in-hand with technologly static religiously devout Amish. They listen to their doctor.
So would you take advice from Amish person about iphones?
Earlier quoted context omitted.
Seems like pretty straightforward exploitation akin to deepfakes. A repository of his work that you can search and work with would be perfectly reasonable though (similar to https://huberman.rile.yt/ ). EDIT: Apparently it already exists.
And then someone steals the Dixie Flatline.
How wonderful is that Steve was describing ChatGPT in his speech to the T back in 1983, and the vision is being realized in not so distance future in 2023, after 40 years instead of 50 to 100 years as his prediction: "The problem was, you can’t ask Aristotle a question. And I think, as we look towards the next fifty to one hundred years, if we really can come up with these machines that can capture an underlying spir…
We’ve already seen cases here where, if a doctor had asked ChatGPT, they would’ve diagnosed the disease correctly. The problem wasn’t that the AI wasn’t good enough. The problem was that they never asked the question.
Then, again, having easy access to getting such questions answered – maybe that makes more people ask such questions?
I have a thing for not taking advice from someone that doesn't listen to their doctor.
(I know he didn’t invent that single-handedly. But you know what I mean.)