Unite.AI

JULY 19, 2024

These tools help identify when AI makes up information or gives incorrect answers, even if they sound believable. These tools use various techniques to detect AI hallucinations. Some rely on machine learning algorithms, while others use rule-based systems or statistical methods. Automatically detects mislabeled data.

LLM 274

LLM AI AI Data Quality 274

Towards AI

OCTOBER 31, 2024

If you are excited to dive into applied AI, want a study partner, or even want to find a partner for your passion project, join the collaboration channel! Golden_leaves68731 is a senior AI developer looking for a non-technical co-founder to join their venture. If this sounds like you, reach out in the thread!

LLM 116

LLM NLP BERT Large Language Models 116

IBM Journey to AI blog

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Data Ingestion 222

Data Ingestion Data Integration Data Quality LLM 222

Unite.AI

OCTOBER 12, 2023

Could you discuss the types of machine learning algorithms that you work on at LXT? Artificial intelligence solutions are transforming businesses across all industries, and we at LXT are honored to provide the high-quality data to train the machine learning algorithms that power them.

Machine Learning 273

Machine Learning Deep Learning Conversational AI Data Quality 273

IBM Journey to AI blog

DECEMBER 20, 2023

This calls for the organization to also make important decisions regarding data, talent and technology: A well-crafted strategy will provide a clear plan for managing, analyzing and leveraging data for AI initiatives. Establish a data governance framework to manage data effectively.

AI Strategy 224

AI Strategy Artificial Intelligence Artificial Intelligence Machine Learning 224

AWS Machine Learning Blog

JANUARY 28, 2025

Furthermore, evaluation processes are important not only for LLMs, but are becoming essential for assessing prompt template quality, input data quality, and ultimately, the entire application stack. It consists of three main components: Data config Specifies the dataset location and its structure.

LLM 98

LLM Large Language Models ML Algorithm 98

Unite.AI

SEPTEMBER 12, 2024

Traditionally, AI research and development have focused on refining models, enhancing algorithms, optimizing architectures, and increasing computational power to advance the frontiers of machine learning. However, a noticeable shift is occurring in how experts approach AI development, centered around Data-Centric AI.

Data Quality 157

Data Quality Data Scarcity AI AI 157

Snorkel AI

MARCH 4, 2025

These preferences are then used to train a reward model , which predicts the quality of new outputs. Finally, the reward model guides the LLMs behavior using reinforcement learning algorithms, such as Proximal Policy Optimization (PPO). Data quality dependency: Success depends heavily on having high-quality preference data.

LLM 52

LLM Large Language Models Data Quality Prompt Engineer 52

Towards AI

FEBRUARY 18, 2025

That said, Ive noticed a growing disconnect between cutting-edge AI development and the realities of AI application developers. This belief has not only created barriers for application developers but also raised serious questions about the sustainability of AI progress. Take, for example, the U.S.

ML Engineer 100

ML Engineer LLM Data Quality Algorithm 100

Unite.AI

MAY 3, 2024

Considering the Prolific business model, what are your thoughts on the essential role of human feedback in AI development, especially in areas like bias detection and social reasoning improvement? Human feedback in AI development is crucial. The importance of data quality cannot be overstated for AI systems.

Data Quality 130

Data Quality AI Research AI Researcher AI Development 130

Marktechpost

JULY 22, 2024

This separation hampers the ability to enhance data and models simultaneously, which is essential for improving AI capabilities. Current methods for developing multi-modal generative models typically focus either on refining algorithms and model architectures or enhancing data processing techniques.

Generative AI 105

Generative AI AI Modeling Categorization AI 105

Marktechpost

OCTOBER 7, 2024

Despite achieving performance comparable to transformers, these methods often involve complex algorithms and require specialized techniques for efficient implementation. indicating strong results across varying levels of data quality. while the minGRU scored 79.4, If you like our work, you will love our newsletter.

Neural Network 106

Neural Network Natural Language Processing Machine Learning Data Quality 106

AWS Machine Learning Blog

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

Responsible AI 107

Responsible AI Prompt Engineer Prompt Engineering AI 107

Pickl AI

DECEMBER 25, 2024

The dataset is openly accessible, making it a go-to resource for researchers and developers in Artificial Intelligence. EleutherAI, an independent research organisation dedicated to open-source AI, developed the Pile dataset. These features make the Pile a benchmark dataset for cutting-edge AI development.

Large Language Models 52

Large Language Models Natural Language Processing AI Research AI Researcher 52

Towards AI

APRIL 2, 2024

So far, LLM capability improvements have been relatively predictable with compute and training data scaling — and this likely gives confidence to plan projects on this $100bn scale. However, the AI community has also been making a lot of progress in developing capable, smaller, and cheaper models. Why should you care?

LLM 103

LLM OpenAI Explainable AI AI 103

AWS Machine Learning Blog

NOVEMBER 16, 2023

For many years, Philips has been pioneering the development of data-driven algorithms to fuel its innovative solutions across the healthcare continuum. Also in patient monitoring, image guided therapy, ultrasound and personal health teams have been creating ML algorithms and applications.

Data Scientist 110

Data Scientist ML Data Science Machine Learning 110

Pickl AI

DECEMBER 16, 2024

With the global AI market exceeding $184 billion in 2024a $50 billion leap from 2023its clear that AI adoption is accelerating. This blog aims to help you navigate this growth by addressing key enablers of AI development. Key Takeaways Reliable, diverse, and preprocessed data is critical for accurate AI model training.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Algorithm 52

Pickl AI

JULY 12, 2024

Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development. It includes Python and a vast collection of pre-installed libraries and tools for AI development.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Neural Network 52

NVIDIA

JULY 13, 2023

This set off demand for generative AI applications that help businesses become more efficient, from providing consumers with answers to their questions to accelerating the work of researchers as they seek scientific breakthroughs, and much, much more. Now, generative AI can do the heavy lifting.

Generative AI 98

Generative AI AI AI Natural Language Processing 98

Snorkel AI

MARCH 4, 2025

These preferences are then used to train a reward model , which predicts the quality of new outputs. Finally, the reward model guides the LLMs behavior using reinforcement learning algorithms, such as Proximal Policy Optimization (PPO). Data quality dependency: Success depends heavily on having high-quality preference data.

LLM 59

LLM Large Language Models Data Quality Prompt Engineer 59

Marktechpost

DECEMBER 11, 2024

Preference optimization was then employed using Direct Preference Optimization (DPO) and other algorithms to align the models with human preferences. Image Source : LG AI Research Blog ([link] Responsible AI Development: Ethical and Transparent Practices The development of EXAONE 3.5 model scored 70.2.

AI Research 85

AI Research AI Researcher Generative AI AI 85

Pickl AI

JUNE 23, 2023

In the world of artificial intelligence (AI), data plays a crucial role. It is the lifeblood that fuels AI algorithms and enables machines to learn and make intelligent decisions. And to effectively harness the power of data, organizations are adopting data-centric architectures in AI.

Continuous Learning 52

Continuous Learning Data Quality AI AI 52

Pickl AI

NOVEMBER 3, 2023

Artificial Intelligence (AI) has gone beyond science fiction. It is now the foundation for intelligent, data-driven decisions in present-day stock trading. Forecasts indicate that during the next five years, the global algorithmic trading market is expected to increase at a consistent rate of 8.53%. Isn’t that remarkable?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

John Snow Labs

OCTOBER 19, 2023

With these algorithms being used to make important decisions in various fields, it is crucial to address the potential for unintended bias to affect their outcomes. One reason for this bias is the data used to train these models, which often reflects historical gender inequalities present in the text corpus.

NLP 52

NLP Natural Language Processing Machine Learning AI 52

ODSC - Open Data Science

NOVEMBER 13, 2023

Predictive analytics is rapidly becoming indispensable in data-driven decision-making, especially grant funding. It uses statistical algorithms and machine learning techniques to analyze historical data and predict future outcomes. According to a report by Gartner, poor data quality costs businesses an average of $12.9

Data Science 52

Data Science Categorization Data Quality Machine Learning 52

Snorkel AI

APRIL 25, 2023

I’m excited today to be talking about DataPerf, which is about building benchmarks for data-centric AI development. Why are benchmarks critical for accelerating development in any particular space? What kind of algorithms are you using to run your models? And ultimately, of course, there is data.

Machine Learning 52

Machine Learning Algorithm ML Data Quality 52

Snorkel AI

APRIL 25, 2023

I’m excited today to be talking about DataPerf, which is about building benchmarks for data-centric AI development. Why are benchmarks critical for accelerating development in any particular space? What kind of algorithms are you using to run your models? And ultimately, of course, there is data.

Machine Learning 52

Machine Learning Algorithm ML Data Quality 52

Viso.ai

DECEMBER 18, 2023

Generation With Statistical Distribution A simple way to generate data is with a statistical distribution matching the real data distribution. This involves analyzing the statistical properties of real data, such as mean, variance, and distribution type. This involves analyzing and mapping the behavior of real data.

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52

Snorkel AI

JANUARY 31, 2023

Snorkel AI provides a data-centric AI development platform for AI teams to unlock production-grade model quality and accelerate time-to-value for their investments. Alibi Explain provides a suite of explainability algorithms that work across tabular, text, and image data.

Data Drift 52

Data Drift Explainability Data Scientist AI 52

Snorkel AI

JANUARY 31, 2023

Snorkel AI provides a data-centric AI development platform for AI teams to unlock production-grade model quality and accelerate time-to-value for their investments. Alibi Explain provides a suite of explainability algorithms that work across tabular, text, and image data.

Data Drift 52

Data Drift Explainability Data Scientist AI 52

Topbots

SEPTEMBER 11, 2023

Often, companies assume that all they need to include AI in their offering is to hire AI experts and let them play the technical magic. Over the years, I have seen a great deal of frustration from data scientists and engineers whose technically outstanding AI implementations did not find their way into user-facing products.

UX Design 59

UX Design AI AI Automation 59

Bugra Akyildiz

AUGUST 3, 2024

Data Quality and Processing: Meta significantly enhanced their data pipeline for Llama 3.1: models for enhanced security Sample Applications: Developed reference implementations for common use cases (e.g., Data Quality and Processing: Meta significantly enhanced their data pipeline for Llama 3.1:

Neural Network 52

Neural Network Prompt Engineer Prompt Engineering Large Language Models 52

Topbots

DECEMBER 19, 2023

Presenters from various spheres of AI research shared their latest achievements, offering a window into cutting-edge AI developments. In this article, we delve into these talks, extracting and discussing the key takeaways and learnings, which are essential for understanding the current and future landscapes of AI innovation.

Computer Vision 52

Computer Vision Natural Language Processing AI Research AI Researcher 52

Pickl AI

FEBRUARY 4, 2025

Quality Control in Manufacturing Manufacturers use the empirical formula in quality control processes to monitor product consistency and identify defects. By analysing production data, quality control teams can determine whether products meet specified standards.

Data Quality 52

Data Quality Machine Learning Data Science Algorithm 52

Dlabs.ai

SEPTEMBER 24, 2024

Instead of applying uniform regulations, it categorizes AI systems based on their potential risk to society and applies rules accordingly. This tiered approach encourages responsible AI development while ensuring appropriate safeguards are in place.

AI 52

AI AI Explainability Artificial Intelligence 52

Viso.ai

JUNE 24, 2024

These models usually use a classification algorithm like a Convolutional Neural Network (CNN) or a multimodal architecture. Building an AI for the Blind To build an AI solution that is particularly helpful for the blind, we need to consider a few aspects that can differ from normal AI developments.

Computer Vision 40

Computer Vision Convolutional Neural Networks AI AI 40

Snorkel AI

FEBRUARY 27, 2023

But I want to at least give our perspective on what motivated us back in 2015 to start talking about this and to start studying it back at Stanford, where the Snorkel team started: this idea of a shift from model-centric to data-centric AI development. From there, the key part, of course, is iterating as quickly as possible.

Machine Learning 52

Machine Learning Large Language Models AI AI 52