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Innovations in Analytics: Elevating Data Quality with GenAI

Towards AI

Image Credits: Pixabay Although AI is often in the spotlight, the focus on strong data foundations and effective data strategies is often overlooked. Flipping the paradigm: Using AI to enhance data quality What if we could change the way we think about data quality? Clean data through GenAI!

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Bytedance Researchers Present Cross Language Agent – Simultaneous Interpretation (CLASI): A High-Quality And Human-Like Simultaneous Speech Translation (SiST) System

Marktechpost

There has been a lot of buzz about machine-assisted autonomous interpretation in natural language processing (NLP). They use a three-stage training methodology—pretraining, ongoing training, and fine-tuning—to tackle the data scarcity of the SiST job. It is possible to train the model to skip extra steps in the future.

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Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

The entire process can be further automated incorporating automatic image tagging using modules like RAM or Tag2Text. SegGPT Many successful approaches from NLP are now being translated into computer vision. Comparison of few-shot inference between NLP and CV. Note that we still have to provide textual description.

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Innovations in AI: How Small Language Models are Shaping the Future

Pickl AI

Small Language Models (SLMs) are a subset of AI models specifically tailored for Natural Language Processing (NLP) tasks. Customer Service Automation SLMs power chatbots that handle customer inquiries efficiently, providing quick responses based on specific queries. What Are Small Language Models (SLMs)?

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Multilingual Synthetic Training Data For Intent Detection

Bitext

Recognize a user´s intent in any chatbot platform: Dialogflow, MS-LUIS, RASA… Enjoy 90% accuracy, guaranteed by SLA Machine Learning is one of the most common use cases for Synthetic Data today, mainly in images or videos. Bitext has solutions for your current bot and for your new bot.

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AI2 at EMNLP 2023

Allen AI

FACTSCORE can either be based on human evaluation, or be automated, which allows evaluation of a large set of LMs with no human efforts. FACTSCORE allows a more fine-grained evaluation of factual precision, e.g., in the figure, the top model gets a score of 66.7% and the bottom model gets 10.0%, whereas prior work would assign 0.0

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Synthetic Data: A Model Training Solution

Viso.ai

Instead of relying on organic events, we generate this data through computer simulations or generative models. Synthetic data can augment existing datasets, create new datasets, or simulate unique scenarios. Specifically, it solves two key problems: data scarcity and privacy concerns.