Abstract > We study how vision-language models trained on Internet-scale data can be incorporated directly into end-to-end robotic control to boost generalization and enable emergent semantic reasoning. Our goal is to enable a single end-to-end trained model to both learn to map robot observations to actions and enjoy the benefits...
> Palo Alto, CA, June 29th, 2023 – Inflection AI today announced that the company has raised $1.3 billion in a fresh round of funding led by Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and new investor NVIDIA. The new funding brings the total raised by the company to $1.525...
Abstract: > Large language models have been demonstrated to perform complex tasks. However, enabling general inference in the real world, e.g. for robotics problems, raises the challenge of grounding. We propose embodied language models to directly incorporate real-world continuous sensor modalities into language models and thereby establish the link between...
... (read 188 more words →)We study how vision-language models trained on Internet-scale data can be incorporated directly into end-to-end robotic control to boost generalization and enable emergent semantic reasoning. Our goal is to enable a single end-to-end trained model to both learn to map robot observations to actions and enjoy the benefits of large-scale pretraining on language and vision-language data from the web. To this end, we propose to co-fine-tune state-of-the-art vision-language models on both robotic trajectory data and Internet-scale vision-language tasks, such as visual question answering. In contrast to other approaches, we propose a simple, general recipe to achieve this goal: in order to fit both natural language responses and robotic actions into the same
... (read more)Palo Alto, CA, June 29th, 2023 – Inflection AI today announced that the company has raised $1.3 billion in a fresh round of funding led by Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and new investor NVIDIA. The new funding brings the total raised by the company to $1.525 billion.
Along with its partners CoreWeave and NVIDIA, Inflection AI is building the largest AI cluster in the world comprising 22,000 NVIDIA H100 Tensor Core GPUs. In just over a year, Inflection AI has developed one of the most sophisticated large language models in the market to enable people to interact with Pi, your Personal AI (pi.ai), in the most simple, natural way and
I don't think OpenAI's opinion is going to matter as much as the opinions of governments. OpenAI does influence government opinion, but in case there's a disagreement, I don't expect OpenAI to prevail (except perhaps if we're already deep into a takeoff).
OpenAI was recently successful at lobbying against heavy regulation in the E.U.: https://time.com/6288245/openai-eu-lobbying-ai-act/
... (read more)But behind the scenes, OpenAI has lobbied for significant elements of the most comprehensive AI legislation in the world—the E.U.’s AI Act—to be watered down in ways that would reduce the regulatory burden on the company, according to documents about OpenAI’s engagement with E.U. officials obtained by TIME from the European Commission via freedom of information requests.
In several cases,
ChatGPT-4 gets it right.
Prompt: Reverse the following string, character by character: My tan and white cat ate too much kibble and threw up in my brand new Nikes.
GPT-4:
.sekiN wen dnarb ym ni pu werht dna elbbik hcum oot eta tac etihw dna nat yM
Using this prompting method from /u/TheCodingBoy, GPT-4 gets the correct answer:
Prompt 1: We are going to multiply two large numbers together. We will calculate 12345 * 13579. First, I want you to list the digits of the first number and, for each digit, write down a times symbol and the second number and calculate it. Do not output anything other than this.
GPT-4:
1 * 13579 = 13579
2 * 13579 = 27158
3 * 13579 = 40737
4 * 13579 = 54316
5 * 13579 = 67895
Prompt 2: Please verify all those calculations and correct any incorrect ones. After you have done that, do the following:
Output the first result, but with "0000" added at the end.
Output the... (read more)
ChatGPT-4 can solve this without the "counting step-by-step" prompt:
Prompt: How many times does the word "all" occur in the following sentence: "All the lice and all the mice were all very nice to all the mice and all the lice"?
Response:
The word "all" occurs 5 times in the given sentence. Here's the sentence with the occurrences of "all" highlighted:
- All the lice and
- all the mice were
- all very nice to
- all the mice and
- all the lice.
Seems to get it right:
... (read more)First, we'll quickly determine the order of magnitude of the product:
The order of magnitude can be found by counting the number of digits in each number and adding them together. In this case, 152469 has 6 digits and 793432 has 6 digits as well. Therefore, the product will have around 6+6=12 digits.
Next, we'll use a heuristic to estimate the product by rounding to the nearest thousand:
152469 ≈ 152,000 793432 ≈ 793,000
Estimated product: 152,000 * 793,000 = 120,536,000,000
Now, we'll use another heuristic to quickly determine the final three digits of the product:
For this, we can just multiply the last three digits of each number and ignore the rest:
469 *
Using precise mode in Bing Chat:
Prompt: How many times does the word "all" occur in the following sentence: "All the lice and all the mice were all very nice to all the mice and all the lice"? Show your work by counting step-by-step with a running total before answering.
Response:
Sure! Here’s how I counted the occurrences of the word “all” in the sentence:
- “All” (1) the lice and “all” (2) the mice were “all” (3) very nice to “all” (4) the mice and “all” (5) the lice.
So, there are 5 occurrences of the word “all” in that sentence. 😊
Abstract:
... (read more)Large language models have been demonstrated to perform complex tasks. However, enabling general inference in the real world, e.g. for robotics problems, raises the challenge of grounding. We propose embodied language models to directly incorporate real-world continuous sensor modalities into language models and thereby establish the link between words and percepts. Input to our embodied language model are multi-modal sentences that interleave visual, continuous state estimation, and textual input encodings. We train these encodings end-to-end, in conjunction with a pre-trained large language model, for multiple embodied tasks, including sequential robotic manipulation planning, visual question answering, and captioning. Our evaluations show that PaLM-E, a single large embodied multimodal model, can address a variety
https://www.nytimes.com/2023/01/16/technology/chatgpt-artificial-intelligence-universities.html
While grading essays for his world religions course last month, Antony Aumann, a professor of philosophy at Northern Michigan University, read what he said was easily “the best paper in the class.” It explored the morality of burqa bans with clean paragraphs, fitting examples and rigorous arguments.
A red flag instantly went up.
Mr. Aumann confronted his student over whether he had written the essay himself. The student confessed to using ChatGPT, a chatbot that delivers information, explains concepts and generates ideas in simple sentences — and, in this case, had written the paper.
An update: Cruise has been suspended by the California DMV.