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.

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Unite.AI

DECEMBER 17, 2024

In the US alone, generative AI is expected to accelerate fraud losses to an annual growth rate of 32%, reaching US$40 billion by 2027, according to a recent report by Deloitte. Perhaps, then, the response from banks should be to arm themselves with even better tools, harnessing AI across financial crime prevention.

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AI News

MAY 3, 2024

He also cautioned against rushing to deploy generative AI solutions without properly assessing feasibility and business viability, stating, “We need to pay at least as much attention to whether it should be built as we do to whether it can be built.”

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Unite.AI

DECEMBER 20, 2024

As the demand for generative AI grows, so does the hunger for high-quality data to train these systems. Scholarly publishers have started to monetize their research content to provide training data for large language models (LLMs). AI developers need to take responsibility for the data they use.

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Towards AI

OCTOBER 31, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! We’re also excited to share updates on Building LLMs for Production, now available on our own platform: Towards AI Academy. Wildgamingyt is looking for someone to learn AI with and build projects.

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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.

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IBM Journey to AI blog

MAY 8, 2023

Artificial intelligence (AI) is polarizing. In my previous post , I described the different capabilities of both discriminative and generative AI, and sketched a world of opportunities where AI changes the way that insurers and insured would interact. It excites the futurist and engenders trepidation in the conservative.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. The following diagram shows the Tecton declarative framework.

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O'Reilly Media

NOVEMBER 28, 2023

Generative AI has been the biggest technology story of 2023. And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. Many AI adopters are still in the early stages. What’s the reality?

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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. Luckily, I have an excellent team that is very adept at creating and tailoring solutions to our clients' often-specialized AI data needs.

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Unite.AI

JULY 19, 2024

That's an AI hallucination, where the AI fabricates incorrect information. Studies show that 3% to 10% of the responses that generative AI generates in response to user queries contain AI hallucinations. It integrates smoothly with other products for a more comprehensive AI development environment.

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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.

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Unite.AI

JUNE 12, 2024

Regulatory Needs : A substantial majority (88%) of respondents support increased government oversight of AI, particularly in areas related to security (72%) and privacy (64%). Trust in Data Quality Data Quality Issues : Many IT professionals are cautious about the quality of data used in AI systems.

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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.

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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.

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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. The engine driving generative AI is accelerated computing.

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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. In their methodology, the researchers implemented a hierarchical data pyramid, categorizing data pools based on their ranked model metric scores.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Whether youre new to AI development or an experienced practitioner, this post provides step-by-step guidance and code examples to help you build more reliable AI applications. He specializes in designing, building, and optimizing large-scale data solutions.

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LLM Large Language Models Natural Language Processing Machine Learning 124

Flipboard

FEBRUARY 19, 2025

Responsible AI The AWS approach to responsible AI represents a comprehensive framework built on eight essential pillars designed to foster ethical and trustworthy AI development. Focus should be placed on data quality through robust validation and consistent formatting.

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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. Research AI use cases to know where and how these technologies are being applied in relevant industries.

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Unite.AI

JULY 24, 2024

Generative AI, in particular, has become increasingly popular, with tools like ChatGPT reaching 100 million users just two months after it launched. But these advanced AI solutions are nothing without meaningful, quality data. million annually.

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Marktechpost

DECEMBER 11, 2024

Image Source : LG AI Research Blog ([link] Responsible AI Development: Ethical and Transparent Practices The development of EXAONE 3.5 models adhered to LG AI Research s Responsible AI Development Framework, prioritizing data governance, ethical considerations, and risk management.

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Unite.AI

MARCH 14, 2024

This meticulously crafted executive survey not only charts the accelerated journey of AI integration across industries but also illuminates the transformative shifts towards operational excellence and the rising tide of generative AI technologies.

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Marktechpost

JUNE 15, 2024

NVIDIA has recently unveiled the Nemotron-4 340B , a groundbreaking family of models designed to generate synthetic data for training large language models (LLMs) across various commercial applications. This model can create varied and realistic data outputs, which can then be refined using the Nemotron-4 340B Reward model.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

We conclude by identifying the ongoing efforts to enable the platform with generative AI workloads and rapidly onboard new users and teams to adopt the platform. Customer context Philips uses AI in various domains, such as imaging, diagnostics, therapy, personal health, and connected care.

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Towards AI

APRIL 2, 2024

This is only clearer with this week’s news of Microsoft and OpenAI planning a >$100bn 5 GW AI data center for 2028. This would be its 5th generation AI training cluster. However, the AI community has also been making a lot of progress in developing capable, smaller, and cheaper models.

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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.

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TheSequence

DECEMBER 15, 2024

. 📝 Editorial: Models, Models, Models: The Most Amazing Week in Gen AI Releases As we are approaching the holidays it seems that every major AI lab decided to release their latest models. This efficiency is attributed to advancements in training techniques and the utilization of high-quality synthetic datasets.

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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.

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ODSC - Open Data Science

OCTOBER 2, 2024

You’ll also explore how European initiatives can facilitate the exchange of data and knowledge, driving innovation at the intersection of social sciences and AI technologies. As a result, the evaluation step is often neglected leading to pointless iterations and a lack of knowledge on the true performance of the product.

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Snorkel AI

JANUARY 9, 2024

Snorkel offers a full suite of third-party data connectors, making data stored in popular cloud repositories like Databricks quickly and easily accessible for data-centric AI development with Snorkel Flow.

Machine Learning 52

Machine Learning Large Language Models Data Scientist Data Quality 52

Snorkel AI

OCTOBER 4, 2023

Some may choose to experiment with non-traditional data sources like digital footprints or recurring streaming payments to predict repayment behavior. How foundation models jumpstart AI development Foundation models (FMs) represent a massive leap forward in AI development.

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Snorkel AI

JANUARY 9, 2024

Snorkel offers a full suite of third-party data connectors, making data stored in popular cloud repositories like Databricks quickly and easily accessible for data-centric AI development with Snorkel Flow.

Machine Learning 52

Machine Learning Large Language Models Data Scientist LLM 52

Snorkel AI

OCTOBER 4, 2023

Some may choose to experiment with non-traditional data sources like digital footprints or recurring streaming payments to predict repayment behavior. How foundation models jumpstart AI development Foundation models (FMs) represent a massive leap forward in AI development.

Data Scientist 59

Data Scientist AI AI Neural Network 59

Snorkel AI

OCTOBER 4, 2023

Some may choose to experiment with non-traditional data sources like digital footprints or recurring streaming payments to predict repayment behavior. How foundation models jumpstart AI development Foundation models (FMs) represent a massive leap forward in AI development. See what Snorkel option is right for you.

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ODSC - Open Data Science

FEBRUARY 11, 2025

Building Real-World Applications: Lessons andMistakes Chip Huyen candidly shared common mistakes she has observed in AI application development: Overengineering: Many teams rush to use generative AI for tasks that simpler methods, such as decision trees, could handle more effectively. Focus on data quality over quantity.

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AI Engineer Machine Learning Software Engineer Prompt Engineer 52

ODSC - Open Data Science

SEPTEMBER 27, 2024

Open Data Science AI News Blog Recap DOD Urged to Accelerate AI Adoption Amid Rising Global Threats ( Source ) Anthropic Eyes $40 Billion Valuation in New Funding Round ( Source ) Meta to Launch AI Celebrity Voices from Judi Dench, John Cena, and Other Celebrities ( Source ) Celebrities Fall Victim to ‘Goodbye Meta AI’ Hoax as Fake Privacy Message (..)

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