IBM Journey to AI blog

MAY 9, 2023

It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know. Traditional AI tools, while powerful, can be expensive, time-consuming, and difficult to use. Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models.

Data Platform 347

Data Platform Automation AI AI 347

Unite.AI

SEPTEMBER 23, 2024

McKinsey Global Institute estimates that generative AI could add $60 billion to $110 billion annually to the sector. From technical limitations to data quality and ethical concerns, it’s clear that the journey ahead is still full of obstacles. But while there’s a lot of enthusiasm, significant challenges remain.

Generative AI 290

Generative AI Data Quality AI AI 290

Unite.AI

JANUARY 9, 2024

While the stakes may not be as high for RCM as they are on the clinical side, the repercussions of poorly designed AI solutions are nonetheless significant. Poorly trained AI tools being used to conduct prospective claims audits might miss instances of undercoding, which means missed revenue opportunities. Continuous training.

Metadata 284

Metadata AI AI AI Tools 284

Unite.AI

FEBRUARY 17, 2025

At the next level, AI agents go beyond predictive AI algorithms and software with their ability to operate autonomously, adapt to changing environments, and make decisions based on both pre-programmed rules and learned behaviors.

Automation 144

Automation Responsible AI Generative AI AI Modeling 144

IBM Journey to AI blog

JANUARY 9, 2024

The emergence of generative AI prompted several prominent companies to restrict its use because of the mishandling of sensitive internal data. According to CNN, some companies imposed internal bans on generative AI tools while they seek to better understand the technology and many have also blocked the use of internal ChatGPT.

Data Ingestion 222

Data Ingestion Data Integration Data Quality LLM 222

IBM Journey to AI blog

MAY 8, 2023

Should the parameters of an algorithm be leaked, a third party may be able to copy the model, causing economic and intellectual property loss to the owner of the model. This is to ensure the AI model captures data inputs and usage patterns, required validations and testing cycles, and expected outputs.

Algorithm 218

Algorithm AI AI Data Quality 218

Unite.AI

FEBRUARY 21, 2025

AI relies on high-quality, structured data to generate meaningful insights, but many businesses struggle with fragmented or incomplete product information. Akeneos Product Cloud solution has PIM, syndication, and supplier data manager capabilities, which allows retailers to have all their product data in one spot.

Natural Language Processing 144

Natural Language Processing NLP Categorization Algorithm 144

Marktechpost

DECEMBER 3, 2024

In a world where AI models depend on the quality of the data they receive, having a tool that minimizes data loss is crucial. Parsing documents manually is not only inefficient but also prone to errors and data omissions. Check out the GitHub Page. Don’t Forget to join our 60k+ ML SubReddit.

LLM 102

LLM AI Tools Large Language Models Data Ingestion 102

Marktechpost

MARCH 6, 2025

The research team introduced two model variants: Babel-9B, optimized for efficiency in inference and fine-tuning, and Babel-83B, which establishes a new benchmark in multilingual NLP. Unlike previous models, Babel includes widely spoken but often overlooked languages such as Bengali, Urdu, Swahili, and Javanese.

Large Language Models 67

Large Language Models LLM NLP Data Quality 67

Flipboard

JANUARY 21, 2025

The deployment of generative AI tools across enterprise software has driven a rise in the need for skills related to AI modeling and data annotation amid the full lifecycle of AI solutions, according to Upwork. The workforce needs to build resiliency. They need to learn how to upskill, she said.

Data Mining 128

Data Mining Data Extraction Prompt Engineer Prompt Engineering 128

Unite.AI

SEPTEMBER 18, 2024

AI systems continuously learn and improve by analysing outcomes and adjusting their algorithms, ensuring the lead-scoring process remains accurate and relevant. For instance, AI models can be trained on positive and negative responses, helping sales representatives focus on more productive conversations.

Automation 196

Automation AI AI Algorithm 196

Pickl AI

JANUARY 12, 2025

How they Intersect in Modern Applications Many of these data-driven and AI-driven approaches have begun further to reinforce each other’s strengths in modern applications. Data forms the backbone of AI systems, feeding into the core input for machine learning algorithms to generate their predictions and insights.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Explainability Explainable AI 52

Unite.AI

APRIL 23, 2024

At Aiimi, we believe that AI should give users more, not less, control over their data. AI should be a driver of data quality and brand-new insights that genuinely help businesses make their most important decisions with confidence. The risks of ‘shadow’ AI can be substantial for businesses.

Insight Engine 130

Insight Engine Auto-complete AI Tools Data Quality 130

Marktechpost

APRIL 15, 2024

Use Cases and Examples Examples of Machine Learning Applications in Climate Change Mitigation Existing Challenges For The Domain and Possible Future Directions Despite the promising applications, there are inherent challenges in the widespread adoption of AI in climate change mitigation.

Machine Learning 106

Machine Learning Data Analysis ML Artificial Intelligence 106

Unite.AI

DECEMBER 27, 2023

The sheer size and complexity of LLMs require extensive training data to operate effectively across various domains and tasks. The quality and quantity of this data will greatly impact the performance of LLMs, and by extension, a company’s suite of AI tools. is absolutely massive.”

LLM 130

LLM AI AI Large Language Models 130

AssemblyAI

AUGUST 3, 2023

The rise of Large Language Models (LLMs) is revolutionizing how we interact with technology. The exploding popularity of conversational AI tools has also raised serious concerns about AI safety. RLHF as Human Preference Tuning RLHF is about teaching an AI model to understand human values and preferences.

LLM 238

LLM ChatGPT Chatbots OpenAI 238

Unite.AI

JANUARY 23, 2025

AI tools have seen widespread business adoption since ChatGPT's 2022 launch, with 98% of small businesses surveyed by the US Chamber of Commerce using them. One critical framework is the EU AI Act , which mandates clear documentation, transparency, and governance for high-risk AI systems.

Responsible AI 111

Responsible AI AI Tools Data Quality Data Analysis 111

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Marktechpost

AUGUST 10, 2024

High-Risk AI: These include critical applications like medical AI tools or recruitment software. They must meet strict standards for accuracy, security, and data quality, with ongoing human oversight. These entities will work together to ensure regulatory uniformity and solve new difficulties in AI governance.

Artificial Intelligence 132

Artificial Intelligence Artificial Intelligence AI AI 132

ODSC - Open Data Science

NOVEMBER 20, 2024

Understanding Prompt Engineering and the Evolution of Generative AI A particularly intriguing part of the conversation touched upon prompt engineering, a skill Yves believes will eventually phase out as generative AI models evolve. Yves Mulkers stressed the need for clean, reliable data as a foundation for AI success.

Generative AI 71

Generative AI Prompt Engineer Prompt Engineering Data Quality 71

Unite.AI

JUNE 17, 2024

By cultivating these three competencies, individuals can navigate the AI era with confidence and create their own irreplaceable value proposition. How can organizations ensure that AI tools are augmenting rather than replacing human workers? Another critical factor is to involve employees in the AI implementation process.

Automation 144

Automation Artificial Intelligence Artificial Intelligence Generative AI 144

Marktechpost

SEPTEMBER 11, 2024

AI models, such as language models, need to maintain a long-term memory of their interactions to generate relevant and contextually appropriate content. One of the primary challenges in maintaining a long-term memory of their interactions is data storage and retrieval efficiency.

Natural Language Processing 60

Natural Language Processing Data Extraction Data Quality Chatbots 60

NVIDIA

JULY 13, 2023

Researchers are now using generative AI models to read a protein’s amino acid sequence and accurately predict the structure of target proteins in seconds, rather than weeks or months. Generative AI can support customers and employees at every step through the buyer journey.

Generative AI 98

Generative AI AI AI Natural Language Processing 98

Unite.AI

JUNE 24, 2024

And with synthetic data then you can avoid privacy issues, and fill in the gaps in training data that’s small or incomplete. This can be helpful for training a more domain-specific generative AI model, and can even be more effective than training a “larger” model, with a greater level of control.

Data Scientist 130

Data Scientist Large Language Models Machine Learning Software Engineer 130

TransOrg Analytics

MAY 16, 2024

To effectively integrate AI into customer segmentation, CPG companies should consider the following steps: Data Consolidation: Collect and unify data from various sources, including sales, customer service interactions, online engagement, and third party demographic information.

Data Quality 52

Data Quality Machine Learning AI AI 52

Defined.ai blog

SEPTEMBER 7, 2023

Consider them the encyclopedias AI algorithms use to gain wisdom and offer actionable insights. The Importance of Data Quality Data quality is to AI what clarity is to a diamond. A healthcare dataset, filled with accurate and relevant information, ensures that the AI tool it trains is precise.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Pickl AI

OCTOBER 2, 2024

Summary: Artificial Intelligence (AI) is revolutionising Genomic Analysis by enhancing accuracy, efficiency, and data integration. Despite challenges like data quality and ethical concerns, AI’s potential in genomics continues to grow, shaping the future of healthcare.

Neural Network 52

Neural Network Deep Learning Machine Learning Artificial Intelligence 52

O'Reilly Media

NOVEMBER 28, 2023

Few nonusers (2%) report that lack of data or data quality is an issue, and only 1.3% report that the difficulty of training a model is a problem. In hindsight, this was predictable: these are problems that only appear after you’ve started down the road to generative AI. Model degradation is a different concern.

Generative AI 137

Generative AI AI AI Data Analysis 137

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 Neural Network AI 64

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 59

Data Scientist Neural Network AI AI 59

Pickl AI

SEPTEMBER 2, 2024

Generative AI focuses on creating new, original content by learning patterns and distributions from existing data. Generative AI models use techniques like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Autoregressive Models to produce novel content.

Generative AI 52

Generative AI AI AI Machine Learning 52

ODSC - Open Data Science

OCTOBER 25, 2024

Curtis will explore how Cleanlab automatically detects and corrects errors across various datasets, ultimately improving the overall performance of machine learning models. It also highlights the full development lifecycle, from model catalog and prompt flow to GenAIOps along with safe & responsible AI practices.

Data Scientist 52

Data Scientist Software Engineer Automation Machine Learning 52

Topbots

JANUARY 29, 2025

We developed an AI tool that acts as a giant sensor into the airline market, monitoring competitors, trends, and the overall market context. Based on this broad information, the tool now provides tailored innovation recommendations for Lufthansa. The company wanted to systematize and speed up its innovation processes.

AI 52

AI AI Automation Generative AI 52

ODSC - Open Data Science

OCTOBER 16, 2024

The session highlights the use of the open-source Llama-3–8b model to achieve inference speeds of 1,000 tokens per second, showcasing how specialized hardware and optimization techniques can significantly enhance user experience by reducing latency.

LLM 40

LLM Large Language Models Data Quality Responsible AI 40

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 52

Data Scientist AI AI Neural Network 52

Pickl AI

NOVEMBER 3, 2023

Data processing: In order to make well-informed forecasts, AI quickly analyses large datasets, including real-time information from social media and the news. Algorithms for ML: AI models employ ML to adjust and find correlations, gradually improving accuracy. AI tools can support your objectives.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

Viso.ai

OCTOBER 10, 2024

AI models use the data on flooding, earthquakes, or any other natural disasters to identify risk-prone areas. Real-time geospatial data is used to plan evacuation routes, allocate emergency resources, and observe the progress of recovery processes in an emergency.

Computer Vision 52

Computer Vision Machine Learning Algorithm Convolutional Neural Networks 52