Marktechpost
DECEMBER 18, 2024
From enhancing software development processes to managing vast databases, AI has permeated every aspect of software development. As businesses strive to stay competitive, adopting AI tools can streamline workflows, minimize errors, and unlock innovative possibilities.
IBM Journey to AI blog
JULY 10, 2023
Existing sales and service engineers can use language-based generative AI to augment their skills and easily find contextual or industrial knowledge to help them deliver better customer experiences or solve problems faster. For instance, organizations can use AI tools to audit compliance documentation according to relevant audit standards.
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Marktechpost
AUGUST 1, 2023
” This generated text is stored as metadata, enabling more efficient video classification and facilitating search engine accessibility. The impact of Flamingo has already been felt, as hundreds of thousands of newly uploaded Shorts videos have benefited from AI-generated descriptions.
Marktechpost
JULY 15, 2023
Based on the transformer architecture, Vicuna is an auto-regressive language model and offers natural and engaging conversation capabilities. The chatbot is designed for conversation and instruction and excels in summarizing, generating tables, classification, and dialog.
AWS Machine Learning Blog
MARCH 28, 2024
You can deploy this solution with just a few clicks using Amazon SageMaker JumpStart , a fully managed platform that offers state-of-the-art foundation models for various use cases such as content writing, code generation, question answering, copywriting, summarization, classification, and information retrieval.
Mlearning.ai
DECEMBER 19, 2023
Modifying Microsoft Phi 2 LLM for Sequence Classification Task. Transformer-Decoder models have shown to be just as good as Transformer-Encoder models for classification tasks (checkout winning solutions in the kaggle competition: predict the LLM where most winning solutions finetuned Llama/Mistral/Zephyr models for classification).
ODSC - Open Data Science
OCTOBER 11, 2023
For more complex issues like label errors, you can again simply filter out all the auto-detected bad data. For instance, when fine-tuning various LLM models on a text classification task (politeness prediction), this auto-filtering improves LLM performance without any change in the modeling code! You can find more details here.
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