Unite.AI

DECEMBER 20, 2024

This raises a crucial question: Are the datasets being sold trustworthy, and what implications does this practice have for the scientific community and generative AI models? These agreements enable AI companies to access diverse and expansive scientific datasets, presumably improving the quality of their AI tools.

Generative AI 130

Generative AI AI Modeling AI AI 130

Unite.AI

MAY 21, 2024

Amidst Artificial Intelligence (AI) developments, the domain of software development is undergoing a significant transformation. Traditionally, developers have relied on platforms like Stack Overflow to find solutions to coding challenges. The emergence of AI “ hallucinations ” is particularly troubling.

AI Developer 147

AI Developer AI Development Software Development Large Language Models 147

Marktechpost

JULY 11, 2024

The rapid advancement in AI technology has heightened the demand for high-quality training data, which is essential for effectively functioning and improving these models. One of the significant challenges in AI development is ensuring that the synthetic data used to train these models is diverse and of high quality.

Data Quality 112

Data Quality Large Language Models AI Modeling Automation 112

Unite.AI

OCTOBER 30, 2023

Improves quality: The effectiveness of AI is significantly influenced by the quality of the data it processes. Training AI models with subpar data can lead to biased responses and undesirable outcomes. Improving AI quality: AI system effectiveness hinges on data quality.

DevOps 310

DevOps Software Development Automation Artificial Intelligence 310

IBM Journey to AI blog

JULY 30, 2024

AI Developer / Software engineers: Provide user-interface, front-end application and scalability support. Organizations in which AI developers or software engineers are involved in the stage of developing AI use cases are much more likely to reach mature levels of AI implementation. Use watsonx.ai

Generative AI 266

Generative AI Data Scientist Software Engineer AI 266

Unite.AI

JANUARY 29, 2024

In the digital era, misinformation has emerged as a formidable challenge, especially in the field of Artificial Intelligence (AI). As generative AI models become increasingly integral to content creation and decision-making, they often rely on open-source databases like Wikipedia for foundational knowledge.

Generative AI 204

Generative AI Data Quality AI Modeling AI 204

Unite.AI

JULY 19, 2024

This extensive knowledge base allows for robust AI validation that makes Pythia ideal for situations where accuracy is important. Here are some key features of Pythia: With its real-time hallucination detection capabilities, Pythia enables AI models to make reliable decisions. Automatically detects mislabeled data.

LLM 279

LLM AI AI Data Quality 279

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

IBM Journey to AI blog

MAY 8, 2023

Risk and limitations of AI The risk associated with the adoption of AI in insurance can be separated broadly into two categories—technological and usage. Technological risk—data confidentiality The chief technological risk is the matter of data confidentiality.

Algorithm 218

Algorithm AI AI Generative AI 218

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 162

Data Quality Data Scarcity AI AI 162

Towards AI

FEBRUARY 11, 2025

Author(s): Richie Bachala Originally published on Towards AI. Beyond Scale: Data Quality for AI Infrastructure The trajectory of AI over the past decade has been driven largely by the scale of data available for training and the ability to process it with increasingly powerful compute & experimental models.

Data Quality 54

Data Quality Neural Network ETL Computer Vision 54

Unite.AI

JUNE 12, 2024

The rapid advancement of AI raises questions about data protection, the integrity of AI models, and the safeguarding of proprietary information. Regulatory Needs : A substantial majority (88%) of respondents support increased government oversight of AI, particularly in areas related to security (72%) and privacy (64%).

Data Quality 147

Data Quality Automation AI AI 147

Unite.AI

OCTOBER 12, 2023

Another key takeaway from that experience is the crucial role that data plays, through quantity and quality, as a key driver of AI model capabilities and performance. Throughout my academic and professional experience prior to LXT, I have always worked directly with data.

Machine Learning 278

Machine Learning Deep Learning Conversational AI Data Quality 278

Snorkel AI

DECEMBER 2, 2024

The integration between the Snorkel Flow AI data development platform and AWS’s robust AI infrastructure empowers enterprises to streamline LLM evaluation and fine-tuning, transforming raw data into actionable insights and competitive advantages. Here’s what that looks like in practice.

Data Ingestion 52

Data Ingestion Large Language Models LLM Machine Learning 52

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. Commit to ethical AI initiatives, inclusive governance models and actionable guidelines.

AI Strategy 224

AI Strategy Artificial Intelligence Artificial Intelligence Machine Learning 224

Unite.AI

JULY 24, 2024

Unfortunately, the process of achieving this kind of data is not always simple – companies need to capture and process data in a way that removes bias, and format it to be easily consumed by AI. Poor Data on AI Solutions AI models rely on data to learn patterns, make predictions, and perform tasks.

AI 147

AI AI AI Modeling Data Quality 147

Marktechpost

JULY 22, 2024

Models are trained on these data pools, enabling in-depth analysis of OP effectiveness and its correlation with model performance across various quantitative and qualitative indicators. The sandbox’s compatibility with existing model-centric infrastructures makes it a versatile tool for AI development.

Generative AI 106

Generative AI AI Modeling Categorization AI 106

Marktechpost

AUGUST 27, 2024

The quantity and quality of data directly impact the efficacy and accuracy of AI models. Getting accurate and pertinent data is one of the biggest challenges in the development of AI. LLMs require current, high-quality internet data to address certain issues.

Data Extraction 101

Data Extraction Automation Linked Data Artificial Intelligence 101

Snorkel AI

MARCH 4, 2025

Alignment ensures that an AI models outputs align with specific values, principles, or goals, such as generating polite, safe, and accurate responses or adhering to a company’s ethical guidelines. LLM alignment techniques come in three major varieties: Prompt engineering that explicitly tells the model how to behave.

LLM 52

LLM Large Language Models Data Quality Prompt Engineering 52

Marktechpost

DECEMBER 6, 2023

Training artificial intelligence (AI) models often requires massive amounts of labeled data. Annotating data is similar to finding a specific grain of sand on a beach. For example, it might look for data the model is unsure about or represent different parts of the overall dataset.

Natural Language Processing 103

Natural Language Processing Deep Learning Artificial Intelligence Artificial Intelligence 103

Marktechpost

AUGUST 10, 2024

It is the world’s first comprehensive milestone in terms of regulation of AI and reflects EU’s ambitions to establish itself as a leader in safe and trustworthy AI development The Genesis and Objectives of the AI Act The Act was first proposed by the EU Commission in April 2021 in the midst of growing concerns about the risks posed by AI systems.

Artificial Intelligence 133

Artificial Intelligence Artificial Intelligence AI AI 133

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. AI Revolution is Losing Steam?

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 Researcher AI Research AI Developer 130

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 111

Responsible AI Prompt Engineering Prompt Engineer AI 111

Unite.AI

JUNE 10, 2024

Josh Wong is the Founder and CEO of ThinkLabs AI. ThinkLabs AI is a specialized AI development and deployment company. Its mission is to empower critical industries and infrastructure with trustworthy AI aimed at achieving global energy sustainability. Josh Wong attended the University of Waterloo.

Continuous Learning 130

Continuous Learning Automation Data Quality AI 130

Pickl AI

MARCH 7, 2025

Summary: The 4 Vs of Big DataVolume, Velocity, Variety, and Veracityshape how businesses collect, analyse, and use data. These factors drive decision-making, AI development, and real-time analytics. Key Takeaways The 4 Vs of Big Data define how businesses handle massive amounts of information. Why does veracity matter?

Big Data 52

Big Data Machine Learning Data Quality Data Science 52

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 Researcher AI Research 52

Towards AI

APRIL 2, 2024

However, the AI community has also been making a lot of progress in developing capable, smaller, and cheaper models. This can come from algorithmic improvements and more focus on pretraining data quality, such as the new open-source DBRX model from Databricks. Why should you care?

LLM 103

LLM OpenAI Explainable AI AI 103

AWS Machine Learning Blog

NOVEMBER 7, 2024

It contains services used to onboard, manage, and operate the environment, for example, to onboard and off-board tenants, users, and models, assign quotas to different tenants, and authentication and authorization microservices. Generative AI model components contain microservices for foundation and custom model invocation operations.

Generative AI 113

Generative AI Machine Learning AI AI 113

Unite.AI

MARCH 14, 2024

The demand for high-quality training data is intensifying , with 66% of respondents anticipating an increase in their training data needs over the next two to five years. This underscores the critical role of data in training more sophisticated and accurate AI models.

Computer Vision 124

Computer Vision AI AI Artificial Intelligence 124

Pickl AI

DECEMBER 16, 2024

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. GPUs, TPUs, and AI frameworks like TensorFlow drive computational efficiency and scalability.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Algorithm 52

Snorkel AI

DECEMBER 2, 2024

The integration between the Snorkel Flow AI data development platform and AWS’s robust AI infrastructure empowers enterprises to streamline LLM evaluation and fine-tuning, transforming raw data into actionable insights and competitive advantages. Heres what that looks like in practice.

Data Ingestion 52

Data Ingestion Large Language Models LLM Machine Learning 52

Snorkel AI

MARCH 4, 2025

Alignment ensures that an AI models outputs align with specific values, principles, or goals, such as generating polite, safe, and accurate responses or adhering to a company’s ethical guidelines. LLM alignment techniques come in three major varieties: Prompt engineering that explicitly tells the model how to behave.

LLM 59

LLM Large Language Models Data Quality Prompt Engineering 59

Pickl AI

JUNE 23, 2023

The Importance of Data-Centric Architecture Data-centric architecture is an approach that places data at the core of AI systems. At the same time, it emphasizes the collection, storage, and processing of high-quality data to drive accurate and reliable AI models. How Does Data-Centric AI Work?

Continuous Learning 52

Continuous Learning Data Quality AI AI 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

Snorkel AI

OCTOBER 4, 2023

ML can significantly reduce the time necessary to pre-process customer data for downstream tasks, like training predictive models. Supercharge predictive modeling. Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency.

Data Scientist 64

Data Scientist AI AI Neural Network 64

O'Reilly Media

NOVEMBER 28, 2023

People with AI skills have always been hard to find and are often expensive. While experienced AI developers are starting to leave powerhouses like Google, OpenAI, Meta, and Microsoft, not enough are leaving to meet demand—and most of them will probably gravitate to startups rather than adding to the AI talent within established companies.

Generative AI 125

Generative AI AI AI Data Analysis 125