[ad_1]
When Lex Friedman visited our MIT AI Enterprise Studio class to speak about the way forward for AI, we acquired into some fairly attention-grabbing concepts in regards to the close to future.
On the high of Lex’s feedback, he talked about disruption – predicting that two new trillion-dollar corporations will emerge out of the AI period, and suggesting that Google, Meta and Microsoft will probably not be capable of pivot shortly sufficient to keep up their dominance.
When it comes to the place we’d see this innovation, one in all his focus factors was on language. Lex identified that in America, we take it as a right that everybody speaks English – however around the globe, there is a gigantic marketplace for actual, exact speech translation. Individuals, he mentioned, converse many languages in an “intimate” method – and that requires precision on the a part of the know-how.
He additionally talked about the way forward for robotics, predicting that we’ll have a whole lot of hundreds of thousands of robots within the house.
“The aim of these robots will not be that can assist you wash the dishes,” he mentioned. “They’ll be your mates, in the identical method canine and cats are.”
Each of his predictions make sense in that they handle extra of the human part of robotic interplay, and never simply your kind of common taskrabbit imaginings in the case of a robotic’s ‘job.’
Previous to that, he was additionally addressing the know-how’s capability for what he referred to as “deep personalization.”
“Something the place there’s interplay happening with a product, all of that needs to be captured, all that needs to be transformed into knowledge,” he mentioned. “And that is going to be the benefit – the algorithms do not matter … you will have to have the ability to fine-tune it to every particular person particular person, and do this, not throughout a single day or single interplay, however throughout a lifetime, the place you share recollections, the low, the highs, and the lows, along with your giant language mannequin.”
That’s a compelling description of how we’re probably to make use of LLMs each day, via our lives, not simply as occasional toys or utilities.
Now, here is the place it acquired actually attention-grabbing – once we requested Lex ‘what are the most effective inquiries to ask your self?’
After pondering a bit, he got here again with this: “what’s one of the simplest ways to have influence?”
He talked about issues like working a podcast, and constructing issues out of code.
He additionally talked about that effective line between being content material and completely satisfied, and at all times being stressed for change, referencing Marvin Minsky’s assertion that he at all times remained unhappy with previous work.
“All the time be grateful,” he mentioned.
Within the meantime, we put the identical query into chatGPT – “what are the most effective inquiries to ask your self?”
Here is the primary a part of what we got here up with:
“In the case of self-reflection, there are a number of thought-provoking questions you may ask your self. Some examples embody: what’s my life’s goal? What’s crucial factor I want to perform in the present day? Do I imagine I am worthy of affection and happiness?”
So there you will have it – the existential response from one in all our foremost impartial media folks and podcasters, and the identical query put to one in all our foremost AI fashions.
Are we going to see extra of this sort of panel exercise within the years to come back, the place you ask people and robots the identical questions, and evaluate their solutions?
The reply is a convincing ‘sure!’
What do you assume? Keep tuned for extra on these thrilling courses, and every little thing else happening in in the present day’s AI world.
[ad_2]
Source link