In a nutshell: As of now Generative AI allows us to automatically poll a consensus from a "stack of documents". Be it a stack of texts (for example ChatGPT) or a stack of images (for example Stable Diffusion) and so forth. The AI's algorithms are an automatization of what polling institutes do "by hand": Instead of engaging a call center doing interviews with thousands of people, polling their response to a query, and then compile a conclusion representing the consensus, the Generative AI polls the conclusion to a query from the stack of documents, representing the consensus, using statistics. Which also explains "hallucinations", because this is basically the result of statistical errors, which you also have in the conclusions of polling institutions. And also which explains why AI itself is not intelligent, as it "only" is a mediator between the intelligence in the documents and its user - much like a polling institute is not an expert in the field of the compiled response from the interviews, as it also is only a mediator. So the thought that Generative AI can do things by itself is simply wrong. What it can do: Polling the information in the documents it was trained with correlated to a topic and compiling a conclusion representing the statistical consensus in the documents. So whatever idea you read in the response of a Generative AI: This idea came from all the authors of the documents. The AI did the work of using statistics to reveal it to you as a mediator.
Here an example for a use case: I formulated a query asking the Generative AI "Claude Instant" to evaluate my comment above. It correlated all the information in regards to the terms used in my comment and compiled the following conclusion, representing the consensus of all documents in its statistical database. Q: "Evaluate the following statement: (citation)" Claude-Instant: "Here is my evaluation of the statement: - It is generally accurate to say that generative AI models like GPT-3 and Stable Diffusion are based on statistically analyzing large datasets of text or images in order to generate likely outputs. They do not have their own internal thoughts or intentions. - Describing the models as "polling" the datasets and compiling a statistical consensus is a reasonable analogy, though not a perfect one. The machine learning algorithms are performing statistical and probabilistic operations on the training data, not literally polling humans. - Saying ideas presented by the AI "came from all the authors of the documents" is valid - the models are regurgitating and recombining ideas seen during training, not generating truly novel ideas. - Comparing generative AI to polling institutions is a useful metaphor for understanding how the models work based on datasets, not their own intelligence, but it is still an analogy - the statistical methods differ from literal polling. - The statement about hallucinations resulting from statistical errors is a reasonable perspective on how flawed or nonsensical outputs can arise from limitations of the generative models. So in summary, while not perfectly describing the technical details, the overall perspective presented in the statement - that generative AI is statistically analyzing training data and acts as a mediator rather than having its own intelligence - seems like a fair evaluation based on my understanding of how these models currently function. The polling/consensus analogy provides a helpful way to conceptualize their capabilities and limitations."
Did you know that the speed of time is the reason Gravity exists.. So far no-one really understands what gravity is, and that is because it is the speed of time... Time is based on the density of the material around it... For instance.. A Black hole has such a dense speed of time, that it has the potential to create Whole universes within itself.. There is a theory that we actually currently exists within a blackhole...
7:06 Just train a bot and set it to auto and let it go through the combos and grow a new virus off old knowledge or just use gene editing and a virus. Maybe use yeast to alter the variants. Im no chemist or scientist but ai can auto create simulations of spongebob while also simulate the characters and data they have connected to. The spongebot is in a simulation but it doesnt know so the sim is reality to it and it grows within.
Science is where the rubber meets the road fo AI. If accomplished, real impact to meet the most vital needs of humanity could be met. If this becomes a reality.
There's some of a problem with doing science "in-virtual", because that virtual setting is artificial, and as such it is strongly biased towards what we already know, towards what our dominant, or even towards what our most popular, theories are /which also probably means older, and not exactly "cutting edge"/, and not towards what is "real", "natural". It's OK for testing, testing theories maybe, to some extent, although the final "word" in this should come from reality itself, from the nature. It should also do pretty well in creating of algorithms, programming probing tools and testing them. But it wouldn't be creating new theories /at least not by working in that capacity/paradigm... maybe hallucinations are some sign it could /eventually/ go beyond that, maybe/. And there'll always be some possibility of AI limiting/cutting off some potential avenues...
The DARPA lady didn't answer your question. Read The Australian Strategic Policy Institute (ASPI) critical technology tracker report to see what countries are leading technology research.
Like, for, you know, literally. A very unconvincing, "I'm a scientist" explanations out the gate. That said, I'm sure he is and it's nerve wracking to be live on film. Keep practicing pitch and Q&As. I hope it works out for you
Finally an Ai interview not about chat bots, image generation, and business productivity. This is the stuff that gets me excited and hopeful.
In a nutshell: As of now Generative AI allows us to automatically poll a consensus from a "stack of documents". Be it a stack of texts (for example ChatGPT) or a stack of images (for example Stable Diffusion) and so forth. The AI's algorithms are an automatization of what polling institutes do "by hand": Instead of engaging a call center doing interviews with thousands of people, polling their response to a query, and then compile a conclusion representing the consensus, the Generative AI polls the conclusion to a query from the stack of documents, representing the consensus, using statistics. Which also explains "hallucinations", because this is basically the result of statistical errors, which you also have in the conclusions of polling institutions. And also which explains why AI itself is not intelligent, as it "only" is a mediator between the intelligence in the documents and its user - much like a polling institute is not an expert in the field of the compiled response from the interviews, as it also is only a mediator.
So the thought that Generative AI can do things by itself is simply wrong. What it can do: Polling the information in the documents it was trained with correlated to a topic and compiling a conclusion representing the statistical consensus in the documents. So whatever idea you read in the response of a Generative AI: This idea came from all the authors of the documents. The AI did the work of using statistics to reveal it to you as a mediator.
Here an example for a use case: I formulated a query asking the Generative AI "Claude Instant" to evaluate my comment above. It correlated all the information in regards to the terms used in my comment and compiled the following conclusion, representing the consensus of all documents in its statistical database.
Q: "Evaluate the following statement: (citation)"
Claude-Instant: "Here is my evaluation of the statement:
- It is generally accurate to say that generative AI models like GPT-3 and Stable Diffusion are based on statistically analyzing large datasets of text or images in order to generate likely outputs. They do not have their own internal thoughts or intentions.
- Describing the models as "polling" the datasets and compiling a statistical consensus is a reasonable analogy, though not a perfect one. The machine learning algorithms are performing statistical and probabilistic operations on the training data, not literally polling humans.
- Saying ideas presented by the AI "came from all the authors of the documents" is valid - the models are regurgitating and recombining ideas seen during training, not generating truly novel ideas.
- Comparing generative AI to polling institutions is a useful metaphor for understanding how the models work based on datasets, not their own intelligence, but it is still an analogy - the statistical methods differ from literal polling.
- The statement about hallucinations resulting from statistical errors is a reasonable perspective on how flawed or nonsensical outputs can arise from limitations of the generative models.
So in summary, while not perfectly describing the technical details, the overall perspective presented in the statement - that generative AI is statistically analyzing training data and acts as a mediator rather than having its own intelligence - seems like a fair evaluation based on my understanding of how these models currently function. The polling/consensus analogy provides a helpful way to conceptualize their capabilities and limitations."
Great explanation, I’ll save it for future reference 👌🏼
Did you know that the speed of time is the reason Gravity exists.. So far no-one really understands what gravity is, and that is because it is the speed of time... Time is based on the density of the material around it... For instance.. A Black hole has such a dense speed of time, that it has the potential to create Whole universes within itself.. There is a theory that we actually currently exists within a blackhole...
7:06 Just train a bot and set it to auto and let it go through the combos and grow a new virus off old knowledge or just use gene editing and a virus. Maybe use yeast to alter the variants. Im no chemist or scientist but ai can auto create simulations of spongebob while also simulate the characters and data they have connected to. The spongebot is in a simulation but it doesnt know so the sim is reality to it and it grows within.
I don't buy it, that guest is generated with AI, I can see it from the lack of textures on the video rendering 🤔
Sometimes the questions are the problem
😂
Science is where the rubber meets the road fo AI. If accomplished, real impact to meet the most vital needs of humanity could be met. If this becomes a reality.
People sure are putting a lots of eggs in the a.i. basket.
There's some of a problem with doing science "in-virtual", because that virtual setting is artificial, and as such it is strongly biased towards what we already know, towards what our dominant, or even towards what our most popular, theories are /which also probably means older, and not exactly "cutting edge"/, and not towards what is "real", "natural". It's OK for testing, testing theories maybe, to some extent, although the final "word" in this should come from reality itself, from the nature. It should also do pretty well in creating of algorithms, programming probing tools and testing them. But it wouldn't be creating new theories /at least not by working in that capacity/paradigm... maybe hallucinations are some sign it could /eventually/ go beyond that, maybe/. And there'll always be some possibility of AI limiting/cutting off some potential avenues...
The DARPA lady didn't answer your question. Read The Australian Strategic Policy Institute (ASPI) critical technology tracker report to see what countries are leading technology research.
Plz dont be "just hype" and Lead to something amazing like treatments for aging, robot assistants. Just a safer world for all in general 😊
Thank you for asking intelligent questions in an articulate way. Great video!
Possibilities .... are You kidding Us!? To steal, cheat and lie ...
a minimum of information and an abundance of beauty salon niceties - thank you for having me - goodbye
Is it just me or does Sam Rodriquez look AI-generated? 🤔
the editor of this piece should be fired, and be sent back to editing 101 courses
Like, for, you know, literally. A very unconvincing, "I'm a scientist" explanations out the gate. That said, I'm sure he is and it's nerve wracking to be live on film. Keep practicing pitch and Q&As. I hope it works out for you