Pickl AI

FEBRUARY 1, 2023

What if we say that you have the option of using a pre-trained model that works as a framework for data training? Yes, Transfer Learning is the answer to it. What is Transfer Learning? Transfer Learning is a technique in Machine Learning where a model is pre-trained on a large and general task.

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Pickl AI

OCTOBER 21, 2024

As industries face the challenge of rapidly evolving data landscapes, ZSL offers a scalable solution that minimises the need for extensive labelling and retraining, making it an essential tool for modern AI applications. Traditional Machine Learning models require extensive labelled datasets for every class they need to predict.

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Pickl AI

MAY 29, 2024

Similarly, multi-task learning can simultaneously tackle multiple tasks like sentiment analysis, named entity recognition, and machine translation in Natural Language Processing, leading to more accurate and efficient language understanding systems. Also read: What is Information Retrieval in NLP? What is Tokenization in NLP?

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Bitext

OCTOBER 6, 2022

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.

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Viso.ai

DECEMBER 18, 2023

Access to synthetic data is valuable for developing effective artificial intelligence (AI) and machine learning (ML) models. Real-world data often poses significant challenges, including privacy, availability, and bias. To address these challenges, we introduce synthetic data as an ML model training solution.

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Pickl AI

OCTOBER 9, 2024

Small Language Models (SLMs) are a subset of AI models specifically tailored for Natural Language Processing (NLP) tasks. This makes advanced NLP capabilities accessible even to smaller organisations. This blog explores the innovations in AI driven by SLMs, their applications, advantages, challenges, and future potential.

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deepsense.ai

FEBRUARY 12, 2024

Supervised learning Supervised learning is a widely used approach in machine learning, where algorithms are trained using a large number of input examples paired with their corresponding expected outputs. SegGPT Many successful approaches from NLP are now being translated into computer vision. Source: own study.

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Allen AI

DECEMBER 4, 2023

They design a suite of tests based on AmbiEnt, presenting the first evaluation of pretrained LMs to recognize ambiguity and disentangle possible meanings, and encourage the field to rediscover the importance of ambiguity for NLP.

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Viso.ai

FEBRUARY 11, 2024

Viso Suite is the only end-to-end computer vision platform Computer Vision vs. Robotics Vision vs. Machine Vision Computer Vision A sub-field of artificial intelligence (AI) and machine learning , computer vision enhances the ability of machines and systems to derive meaningful information from visual data.

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Viso.ai

FEBRUARY 11, 2024

Viso Suite is the only end-to-end computer vision platform Computer Vision vs. Robotics Vision vs. Machine Vision Computer Vision A sub-field of artificial intelligence (AI) and machine learning , computer vision enhances the ability of machines and systems to derive meaningful information from visual data.

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John Snow Labs

AUGUST 7, 2024

They advocate for the importance of transparency, informed consent protections, and the use of health information exchanges to avoid data monopolies and to ensure equitable benefits of Gen AI across different healthcare providers and patients. However as AI technology progressed its potential within the field also grew.

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John Snow Labs

FEBRUARY 29, 2024

They advocate for the importance of transparency, informed consent protections, and the use of health information exchanges to avoid data monopolies and to ensure equitable benefits of Gen AI across different healthcare providers and patients​​. However as AI technology progressed its potential within the field also grew.

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Marktechpost

OCTOBER 15, 2024

While mental health disorders like anxiety, depression, and schizophrenia affect a vast number of people globally, a significant percentage of those in need do not receive proper care due to resource limitations and privacy concerns surrounding the collection of personalized medical data.

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Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

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Viso.ai

DECEMBER 15, 2023

Symbolic Music Understanding ( MusicBERT ): MusicBERT is based on the BERT (Bidirectional Encoder Representations from Transformers) NLP model. It focuses on generating hip-hop rap lyrics, utilizing NLP and machine learning techniques to produce rhythmically and thematically coherent verses.

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Bitext

AUGUST 23, 2023

We have shown in previous posts why Synthetic Training Data is the best way to boost the accuracy of any chatbot, and the solution to the most important problem of chatbots nowadays: data scarcity , namely, the lack of accurate and useful training data for the problems chatbots want to address.

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AWS Machine Learning Blog

DECEMBER 18, 2024

With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties. To tackle this data scarcity challenge, Fastweb had to build a comprehensive training dataset from scratch to enable effective model fine-tuning.

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