Activating LLMs to make the right API calls in the correct order

Activating LLMs to make the right API calls in the correct order

Until the recent, astonishing success of large language models (LLMS), research into dialogue-based AI systems pursued two main strikes: chatbots or agents capable of open conversation, and task-oriented dialogue models whose goal was to extract arguments for APIs and Complete tasks on behalf of the user. LLMS has enabled huge progress with the first challenge, … Read more

A quick guide to Amazon’s papers on ACL 2024

A quick guide to Amazon's papers on ACL 2024

Like the area of ​​conversation AI generally, Amazon’s papers are dominated at this year’s meeting in Association for Computational Linguistics (ACL) of working with large language models (LLMS). The properties that make LLMS ‘output so extraordinary – such as linguistic flowering and semantic context – are also notorious difficult to quantify; As such, model evaluation … Read more

Accounting for cognitive bias in human evaluation of large language models

Accounting for cognitive bias in human evaluation of large language models

Large language models (LLMs) can generate extremely fluent natural-linguistic texts, and move can fool the human mind into neglecting the quality of the content. For example, psychological studies have that very fluent content can pierce as more truthful and useful than fluid content. Preference for Floating Speech is an example of a Cognitive BiasA shortcut … Read more

How the degradation of the task and less LLMs can make AI more affordable

How the degradation of the task and less LLMs can make AI more affordable

The expanding use of generative-IA applications has accomplished the request for accurate, cost-effective large language models (LLMs). LLMS ‘costs vary significantly based on their size, typically measured by the number of parameters: Change to the next smaller size often results in a cost saving of 70% -90%. However, it is not always a viable opportunity … Read more

Lightweight LLM to Conversion of Text to Structured Data

Lightweight LLM to Conversion of Text to Structured Data

One of the most important features of today’s generative models is their ability to take unstructured, partially unstructured or poorly structured input and convert them into structured ones that comply further. Large Language Models (LLMS) can perform this task if you are quick with all schedule specialties and instructions on how to process input. In … Read more

Life to a prescription of Amazon Pharmacy

Life to a prescription of Amazon Pharmacy

Phase plays an important role in throwing patients’ health, but the process of dispensing medication is far more complicated than it may look. At Amazon Pharmacy, we use artificial intelligence (AI) and advanced technologies to remove this complexity and improve patients’ experiences. The pharmacy challenge When a prescription arrives at a pharmacy, its details must … Read more

The technology behind Amazon’s Genai-Powled Shopping Assistant, Rufus

The technology behind Amazon's Genai-Powled Shopping Assistant, Rufus

[Editor’s note: A condensed version of this blog post appeared previously in IEEE Spectrum] “What do I need for cold weather golf?” “What is the difference between trail shoes and running shoes?” “What’s the best dinosaur toy for a five-year-old beerol?” These are some of the open questions that customers can ask a useful sales … Read more

A quick guide to Amazon’s 50-Plus papers on Emnlp 2024

A quick guide to Amazon's 50-Plus papers on Emnlp 2024

Large Language Models (LLMs) have come to dominate the area of ​​natural-language processing, so it is not surprising that they also dominate the research that Amazon scientists present at this year’s conference on empirical methods in natural-language procedure (Emnlp ). LLM training is the subject with the largest number of Amazon papers, which are closely … Read more

Detoxification of large language models via regularized fine tuning

Detoxification of large language models via regularized fine tuning

Large language models (LLMs) have demonstrated impressive benefits across different tasks, but as it has been clear in several cases, they have the risk of producing inappropriate, unsafe or partial output. When generating resorts, a successful trained LLM must comply with a set of policies specified by its creator; For example, the developer may limit … Read more

Model produces pseudocode for security checks in seconds

Model produces pseudocode for security checks in seconds

One of the ways Amazon Web Services (AWS) helps customers stay secure in their cloud is with the AWS Security Hub, which aggregates, organizes, and prioritizes security alerts from AWS services and third-party tools. These alerts are based on security controls – rules that help ensure the services are configured securely and in accordance with … Read more