Marktechpost

MARCH 17, 2024

Artificial intelligence (AI) is quickly changing our lives and careers, from chatbots communicating with consumers to algorithms suggesting your next movie. A great deal of responsibility, however, is associated with this power. Even the most advanced AI models are susceptible to biases, security flaws, and unforeseen outcomes.

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AWS Machine Learning Blog

DECEMBER 5, 2023

New and powerful large language models (LLMs) are changing businesses rapidly, improving efficiency and effectiveness for a variety of enterprise use cases. Speed is of the essence, and adoption of LLM technologies can make or break a business’s competitive advantage.

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AI News

MARCH 7, 2024

Indeed, as Anthropic prompt engineer Alex Albert pointed out, during the testing phase of Claude 3 Opus, the most potent LLM (large language model) variant, the model exhibited signs of awareness that it was being evaluated. Another major company which takes its responsibilities for ethical AI seriously is Bosch.

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ODSC - Open Data Science

JANUARY 23, 2024

One of the biggest topics we touched on was the concept of retrieval augmented generation, better known as RAG , for LLMs. In this post, I take a closer look at how RAG has emerged as the ideal starting point when it comes to designing enterprise LLM-powered applications. You can imagine it as a pyramid, where… Train from scratch.

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ODSC - Open Data Science

SEPTEMBER 28, 2023

5 Must-Have Skills to Get Into Prompt Engineering From having a profound understanding of AI models to creative problem-solving, here are 5 must-have skills for any aspiring prompt engineer. The Implications of Scaling Airflow Wondering why you’re spending days just deploying code and ML models?

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Marktechpost

MAY 6, 2024

The Llama team’s future goals include extending Llama 3 into multilingual and multimodal domains, boosting contextual understanding, and continuously advancing fundamental LLM functions like code generation and reasoning. In conclusion, Llama3-ChatQA-1.5

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John Snow Labs

SEPTEMBER 5, 2023

Topics Covered Include Large Language Models, Semantic Search, ChatBots, Responsible AI, and the Real-World Projects that Put Them to Work John Snow Labs , the healthcare AI and NLP company and developer of the Spark NLP library, today announced the agenda for its annual NLP Summit, taking place virtually October 3-5.

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Marktechpost

NOVEMBER 23, 2023

During Data Science Conference 2023 in Belgrade on Thursday, 23 November, it was announced that Real AI won the ISCRA project. Real AI is chosen to build Europe’s first-ever Human-Centered LLM on the world’s 4th largest AI Computer Cluster ‘LEONARDO’. – Tarry Singh , CEO of Real AI B.V.

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Unite.AI

MARCH 15, 2024

It uses advanced AI and semantic search technologies to transform online search. Moreover, the search engine uses LLM combined with live data to answer questions and summarize information based on the top sources. AI Summaries: Provides AI generated summaries with images and videos for insights.

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Flipboard

AUGUST 6, 2023

The tool connects Jupyter with large language models (LLMs) from various providers, including AI21, Anthropic, AWS, Cohere, and OpenAI, supported by LangChain. Furthermore, variable interpolation enables dynamic interactions with AI models. Check out the GitHub and Reference Article.

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Unite.AI

JULY 11, 2023

Covers Google tools for creating your own Generative AI apps. You’ll also learn about the Generative AI model types: unimodal or multimodal, in this course. Introduction to Large Language Models Image Source Course difficulty: Beginner-level Completion time: ~ 45 minutes Prerequisites: No What will AI enthusiasts learn?

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ODSC - Open Data Science

FEBRUARY 6, 2024

Large Language Models are everywhere these days. Stay at the forefront of increasingly ubiquitous technology with the leading AI training conference, ODSC East this April 23rd-25th in Boston. Check out some of the LLM-focused training sessions, workshops, and talks you’ll find at the conference.

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ODSC - Open Data Science

JANUARY 10, 2024

The AI Paradigm Shift: Under the Hood of a Large Language Models Valentina Alto | Azure Specialist — Data and Artificial Intelligence | Microsoft Develop an understanding of Generative AI and Large Language Models, including the architecture behind them, their functioning, and how to leverage their unique conversational capabilities.

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John Snow Labs

OCTOBER 19, 2023

Recognizing and addressing sycophantic behavior is crucial in fostering transparency, trustworthiness, and authenticity in AI systems, ultimately benefiting users and society as a whole. “AI AI models, like chameleons, adapt to user opinions, even if it means agreeing with the absurd.

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Towards AI

AUGUST 22, 2023

Last Updated on August 23, 2023 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. This is consistent with the company’s strategy so far of releasing widely available AI software that makes developing new customizable AI models much easier.

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ODSC - Open Data Science

OCTOBER 3, 2023

If you’re unfamiliar, a prompt engineer is a specialist who can do everything from designing to fine-tuning prompts for AI models, thus making them more efficient and accurate in generating human-like text. This role is pivotal in harnessing the full potential of large language models.

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ODSC - Open Data Science

AUGUST 29, 2023

Since OpenAI’s ChatGPT kicked down the door and brought large language models into the public imagination, being able to fully utilize these AI models has quickly become a much sought-after skill. With that said, companies are now realizing that to bring out the full potential of AI, prompt engineering is a must.

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Unite.AI

JANUARY 1, 2024

Knowledge at Your Fingertips Knewton ’s study reveals students utilizing AI-powered adaptive learning programs demonstrated a remarkable 62% improvement in test scores. Generative AI brings knowledge to our immediate access with large language models (LLM) like ChatGPT or Bard.ai.

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Towards AI

NOVEMBER 14, 2023

It is easy to get caught up in the incredible pace of new AI model releases and capability improvements. So, we think it is essential to see detailed studies on AI adoption across industries so we can start to plan for both the positive and negative impacts of this technology. Why should you care?

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ODSC - Open Data Science

JUNE 29, 2023

Debugging Object Detection Models, 8 Trending LLMs, New AI Tools, and Generative AI as a Must-Have Skill Debug Object Detection Models with the Responsible AI Dashboard This blog will focus on the Azure Machine Learning Responsible AI Dashboard’s new vision insights capabilities, supporting debugging capabilities for object detection models.

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ODSC - Open Data Science

DECEMBER 1, 2023

Work with Generative Artificial Intelligence (AI) Models in Azure Machine Learning The purpose of this course is to give you hands-on practice with Generative AI models. You’ll explore the use of generative artificial intelligence (AI) models for natural language processing (NLP) in Azure Machine Learning.

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ODSC - Open Data Science

FEBRUARY 8, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

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ODSC - Open Data Science

JANUARY 29, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. This enhances the context awareness and factual accuracy of LLM outputs.

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AWS Machine Learning Blog

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring.

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Towards AI

APRIL 1, 2023

Last Updated on April 1, 2023 by Editorial Team Author(s): Mary Reagan PhD Originally published on Towards AI. Part 2: Responsible AI Recommendations for ML Practitioners and Policy Makers By Mary Reagan and Krishnaram Kenthapadi This is a follow-up to my part 1 on ChatGPT.

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IBM Journey to AI blog

OCTOBER 16, 2023

It encompasses risk management and regulatory compliance and guides how AI is managed within an organization. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

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AWS Machine Learning Blog

MAY 9, 2024

Governance Establish governance that enables the organization to scale value delivery from AI/ML initiatives while managing risk, compliance, and security. Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI.

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ODSC - Open Data Science

FEBRUARY 5, 2024

This surge is largely due to enhanced support for ONNX models and significant improvements in text embedding calculation, essential for retrieval augmented generation LLM solutions. The NLP Lab platform, a no-code solution for AI model training and publishing, has seen a fivefold increase in usage.

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Marktechpost

JULY 4, 2023

For the unaware, ChatGPT is a large language model (LLM) trained by OpenAI to respond to different questions and generate information on an extensive range of topics. In models like DALLE-2, prompt engineering includes explaining the required response as the prompt to the AI model.

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ODSC - Open Data Science

MARCH 12, 2024

With large language models and generative AI reshaping the digital landscape, what isn’t talked about enough is how these technologies have also revolutionized and significantly shifted the landscape of hardware requirements. Much of which falls under the sub-field of responsible AI.

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ODSC - Open Data Science

MARCH 8, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. The Open-Sora Plan project ‘s aim is to reproduce OpenAI’s Sora.

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John Snow Labs

NOVEMBER 6, 2023

On the other hand, LangTest has emerged as a transformative force in the realm of Natural Language Processing (NLP) and Large Language Model (LLM) evaluation. The toolkit sheds light on a model’s robustness, bias, accuracy, toxicity, fairness, efficiency, clinical relevance, security, disinformation, political biases, and more.

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ODSC - Open Data Science

MARCH 11, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

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Topbots

DECEMBER 5, 2023

Top LLM Research Papers 2023 1. LLaMA by Meta AI Summary The Meta AI team asserts that smaller models trained on more tokens are easier to retrain and fine-tune for specific product applications. The instruction tuning involves fine-tuning the Q-Former while keeping the image encoder and LLM frozen.

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John Snow Labs

JANUARY 25, 2024

John Snow Labs , the AI for healthcare company, has completed its highest growth year in company history. Attributed to its state-of-the-art artificial intelligence (AI) models and proven customer success, the focus on generative AI has gained the company industry recognition.

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Snorkel AI

JUNE 7, 2023

Mann touched on many details of the project—from the mix of the data Bloomberg used to their training sequence to the impact of the numerical precision of gradient estimates to the challenge in evaluating the performance of generative AI models. The output of generative models defies simple comparisons to test sets.

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Snorkel AI

JUNE 7, 2023

Mann touched on many details of the project—from the mix of the data Bloomberg used to their training sequence to the impact of the numerical precision of gradient estimates to the challenge in evaluating the performance of generative AI models. The output of generative models defies simple comparisons to test sets.

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