Lifeboat Foundation

What is Prompt Engineering?

Artificial intelligence, particularly natural language processing, has a notion called prompt engineering (NLP). In prompt engineering, the job description is included explicitly in the input, such as a question, instead of being provided implicitly. Typically, prompt engineering involves transforming one or more tasks into a prompt-based dataset and “prompt-based learning”—also known as “prompt learning”—to train a language model. Prompt engineering, also known as “prefix-tuning” or “prompt tuning,” is a method wherein a big, “frozen” pretrained language model is used, and just the prompt’s representation is learned.

Developing the ChatGPT Tool, GPT-2, and GPT-3 language models was crucial for prompt engineering. Multitask prompt engineering in 2021 has shown strong performance on novel tasks utilizing several NLP datasets. Few-shot learning examples prompt with a thought chain provide a stronger representation of language model thinking. Prepaying text to a zero-shot learning prompt that supports a chain of reasoning, such as “Let’s think step by step,” may enhance a language model’s performance in multi-step reasoning tasks. The release of various open-source notebooks and community-led image synthesis efforts helped make these tools widely accessible.

Common sense priors are essential to make decisions under uncertainty in real-world settings. Let’s say they want to give the scenario in Fig. 1 some labels. As a few key elements are recognized, it becomes evident that the image shows a restroom. This assists in resolving some of the labels for certain more difficult objects, such as the shower curtain in the scene rather than the window curtain and the mirror instead of the portrait on the wall. In addition to visual tasks, prior knowledge of expected item or event co-occurrences is crucial for navigating new environments and comprehending the actions of other agents. Moreover, such expectations are essential to object categorization and reading comprehension.

Unlike robot demos or segmented pictures, vast text corpora are easily accessible and include practically all aspects of the human experience. Current machine learning models use task-specific datasets to learn about the previous distribution of labels and judgments for the majority of problem domains. When training data is skewed or sparse, this can lead to systematic mistakes, particularly on uncommon or out-of-distribution inputs. How might they provide models with broader, more adaptable past knowledge? They suggest using learned distributions over natural language strings known as language models as task-general probabilistic priors.

LMs have been employed as sources of prior knowledge for tasks ranging from common-sense question answering to modeling scripts and tales to synthesizing probabilistic algorithms in language processing and other text production activities. They frequently give higher diversity and fidelity than small, task-specific datasets for encoding much of this information, such as the fact that plates are found in kitchens and dining rooms and that breaking eggs comes before whisking them. It has also been proposed that such language monitoring contributes to common-sense human knowledge in areas that are challenging to learn from first-hand experience.

What’s the scientific reason behind Earth’s sky appearing blue to the human eye?

Scientists said they recorded particles travelling faster than light – a finding that could overturn one of Einstein’s fundamental laws of the universe. Antonio Ereditato, spokesman for the international group of researchers, saidthat measurements taken over three years showed neutrinos pumped from CERN near Geneva to Gran Sasso in Italy had arrived 60 nanoseconds quicker than light would have done.

Researchers have created a new optical illusion that makes your brain try to predict the future — namely, entering a dark tunnel.

Double Jeopardy with False Positives? And how this Relates to the Search for Extraterrestrial Life.

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Putin also said that Russia would suspend its participation in a treaty aimed at keeping a lid on nuclear weapons expansion. The so-called New START Treaty was signed by Russia and the U.S. in 2010. It caps the number of long-range nuclear warheads they can deploy and limits the use of missiles that can carry atomic weapons.

Putin said Tuesday in a major address that Russia was not fully withdrawing from the treaty yet. He said Russia must stand ready to resume nuclear weapons tests if the US does so.

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Out of numerous companies that have created quantum technology, these 6 are particularly known for their work in superconducting qubits.

Such credentials in the wrong hands could be dangerous, experts say, potentially allowing physical access to data centers. The affected data center operators say the stolen information didn’t pose risks for customer IT systems.