gimili
Joined 11 years ago
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298
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37
Member since
Oct 13
Recent submissions
Comment · 3 months ago
I love the word "meat proxy" :)
For me what matters most is whether the person understood the core of the thing they are forwarding. Usually a wall of text is contraindicative of that.
I want my team to be able to write the core idea on a whiteboard without any help before going ahead and sharing or implementing it.
Wrote it up here of when (instead of if) to use AI in any given context: https://assistedeverything.substack.com/p/ai-bowtie
Comment · 4 months ago
Thinking about a similar question, I've tried to come up with this framework:
https://assistedeverything.substack.com/p/ai-bowtie
Maybe it helps in your interviews.
I think you will find that both AI-pilled as well as AI-sceptics will actually agree on that approach, because it rejects the question of "how much" and rather reflects it towards the "when to use AI". Depending on who it is, you can then talk more about the beginning, end or center piece of it.
Comment · 2 years ago
I don't think (a) is a pure UI thing.
Think of the difference of using a single-user application to e.g. make mockups for websites or a collaborative environment like figma, in which you happen to also be able to have AI collaborate with you. Very different usecases and solving collaboration workflows, etc. is non trivial.
I guess for (c) both things will exist. Local will be done for 2 reasons: - data sovereignty (e.g. companies wanting to have applications that are purely trained/fine tuned on their own data; but that improvement is not shared) - privacy (anything from an AI having access to all your email and calendar up to having intimate "friendships" with AI)
Comment · 2 years ago
I think it is more complex than the author thinks.
There are clearly defensible aspects for ai startups. Specifically I think these are: a) in-context and collaborative features (since working alone with ai through a chat box is unlikely the only way we will interact) b) gated knowledge/data (since commonly available technology can be leveraged with unique data) c) edge computing and offline usecases won't be the center piece for many classical companies and therefore can be very well exploited.
I wrote up a framework to assess LLM powered Startups/Ideas here: https://assistedeverything.substack.com/p/the-three-hills-mo...
Comment · 3 years ago
I like the calculation; makes things more clear.
However, to your last point: You are saying that nuclear power plants then are insured to risk. Can you point me in your sources to the place where it is shown how nuclear power plant operators today then are insuring "to risk" the risk of nuclear disaster and all costs and risks of the disposal?
Comment · 3 years ago
Not a hardware startup per-se, but we are ex-satellite engineers who out if frustration with available tooling have developed the engineering software every hardware engineer deserves: https://www.valispace.com
Also just released the first hardware engineering ai assistant: https://youtu.be/uLEOPpqiUok
Comment · 3 years ago
We're taking a shot at hardware engineering: www.valispace.com/ai/
And I see similar things happening for major fields such as education, law, art, software development, management, etc. Here I looked into a few examples of what is happening in these fields already: https://assistedeverything.substack.com/p/the-age-of-assiste...
now leading Altium's Requirements Portal: https://www.altium.com/capabilities/requirements/requirements-management