ODSC - Open Data Science

AUGUST 3, 2023

ML for Big Data with PySpark on AWS, Asynchronous Programming in Python, and the Top Industries for AI Harnessing Machine Learning on Big Data with PySpark on AWS In this brief tutorial, you’ll learn some basics on how to use Spark on AWS for machine learning, MLlib, and more. You Can Now Watch the Generative AI Summit On-Demand Here!

Big Data 52

Big Data Python ML Machine Learning 52

Marktechpost

JULY 31, 2024

In AI, developing language models that can efficiently and accurately perform diverse tasks while ensuring user privacy and ethical considerations is a significant challenge. This work represents a significant advancement in the field, offering a robust framework for future AI developments. Check out the Paper.

Neural Network 117

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Marktechpost

AUGUST 9, 2024

The improved NLP capabilities are expected to significantly enhance user experience, particularly in applications where human-AI interaction is critical, such as customer service, virtual assistants, and automated content generation. AI Ethics and Responsible Innovation In developing EXAONE 3.0, Released: A 7.8B

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Marktechpost

SEPTEMBER 3, 2024

Ethical Considerations and Future Prospects As with any AI model, the release of miniG also raises important ethical considerations. CausalLM has emphasized the importance of responsible AI development and has taken steps to ensure that miniG is used in a manner that aligns with ethical standards.

Natural Language Processing 113

Natural Language Processing Responsible AI AI AI 113

Marktechpost

OCTOBER 16, 2024

DAM proves that focusing on efficiency and scalability without sacrificing performance can provide a significant advantage in AI development. Moving forward, researchers intend to explore DAM’s scalability across different domains and languages, potentially expanding its impact on the broader AI landscape.

Inference Engine 62

Inference Engine Large Language Models AI AI 62

Marktechpost

AUGUST 20, 2024

The core challenge in AI development is the significant manual effort required to design, configure, and fine-tune these systems for specific applications. As AI is applied to more complex and varied tasks, the demand for systems operating efficiently without extensive human intervention becomes critical.

Automation 104

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Marktechpost

JULY 28, 2024

This integration empowers AI developers to leverage the comprehensive capabilities of the TensorOpera AI Platform for cloud-based training and subsequently deploy and personalize these solutions on edge devices via the TensorOpera FedML platform. If you like our work, you will love our newsletter.

Composite AI 117

Composite AI Generative AI AI Developer AI Development 117

Marktechpost

OCTOBER 18, 2024

These advanced models expand AI capabilities beyond text, allowing understanding and generation of content like images, audio, and video, signaling a significant leap in AI development. Don’t Forget to join our 50k+ ML SubReddit. If you like our work, you will love our newsletter.

Large Language Models 91

Large Language Models Inference Engine Natural Language Processing LLM 91

Marktechpost

AUGUST 6, 2024

Such evaluations are critical for developers and researchers aiming to deploy AI systems in real-world applications where reliability is non-negotiable. The introduction of Sphynx underscores the importance of dynamic and rigorous testing in AI development. If you like our work, you will love our newsletter.

Large Language Models 109

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Marktechpost

AUGUST 8, 2024

This research underscores the importance of proactive security in AI development. Check out the Paper. All credit for this research goes to the researchers of this project. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup. If you like our work, you will love our newsletter.

LLM 103

LLM AI Developer AI Development ML 103

Marktechpost

JULY 26, 2024

Standardized, clear, and repeatable benchmarks are becoming increasingly important as AI develops, particularly when it comes to multimodal models. LMMS-EVAL, LMMS-EVAL LITE, and LiveBench are intended to close the gaps in the existing assessment frameworks and facilitate the continuous development of AI.

Large Language Models 104

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Marktechpost

AUGUST 17, 2024

Imagen 3 incorporates extensive safety measures in responsible AI development, including rigorous data curation, risk analysis, and post-training interventions such as safety filters and synthetic captions. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Responsible AI 62

Responsible AI AI AI Automation 62

Marktechpost

SEPTEMBER 23, 2024

OpenAI’s Commitment to Responsible AI Development The MMMLU dataset also reflects OpenAI’s broader commitment to transparency, accessibility, and fairness in AI research. This allows for a more granular understanding of a model’s strengths and weaknesses across different domains.

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ODSC - Open Data Science

SEPTEMBER 26, 2024

Where do explainable AI models come into play? 10 of Our Favorite AI Slides from ODSC Europe 2024 These ten AI slides from ODSC Europe 2024 will teach you plenty about generative AI applications, the AI development lifecycle, RLHF, and plenty more.

Robotics 52

Robotics Data Science Large Language Models AI 52

Marktechpost

JULY 24, 2024

Researchers emphasize the need for policies that evolve with the technology and accurately reflect the complexities of modern AI development. Check out the Paper. All credit for this research goes to the researchers of this project. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

AI 104

AI AI AI Modeling AI Research 104

Marktechpost

AUGUST 7, 2024

By distinguishing genuinely open models from those that are not, the MOF helps ensure that users and researchers can trust and verify the models they work with, promoting responsible AI development. Image Source The MOF also introduces a classification system with three levels: Class I, Class II, and Class III.

Metadata 109

Metadata AI AI AI Research 109

Marktechpost

AUGUST 22, 2024

NVIDIA emphasizes the importance of responsible AI development and encourages users to consider these factors when deploying the model in real-world applications. Like many large language models, it was trained on data that may contain toxic language and societal biases. If you like our work, you will love our newsletter.

AI Modeling 104

AI Modeling Large Language Models Natural Language Processing AI 104

Marktechpost

AUGUST 17, 2024

Two taxonomies were developed: the Causal Taxonomy, categorizing risks by responsible entity, intent, and timing, and the Domain Taxonomy, classifying risks into specific domains. The definition of AI risk, aligned with the Society for Risk Analysis, encompasses potential negative outcomes from AI development or deployment.

Categorization 67

Categorization AI AI Data Extraction 67

Marktechpost

AUGUST 24, 2024

Artificial intelligence (AI) development, particularly in large language models (LLMs), focuses on aligning these models with human preferences to enhance their effectiveness and safety. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup. If you like our work, you will love our newsletter.

AI Modeling 104

AI Modeling AI AI Large Language Models 104

Marktechpost

SEPTEMBER 18, 2024

The researchers also implemented WiM using the Hugging Face Transformers library, making it accessible to a broader audience of AI developers. By releasing the code as open-source, they encourage further experimentation and development of the WiM method. If you like our work, you will love our newsletter.

Large Language Models 104

Large Language Models Natural Language Processing Explainability Artificial Intelligence 104

Marktechpost

AUGUST 18, 2024

This method simplifies the data annotation process and extends its applicability in different domains, making it a versatile tool for AI development. The process is thus automated; hence, SAFER-INSTRUCT enables more diversified and contextually relevant data to be created, enhancing the safety and alignment of language models.

Automation 57

Automation AI Developer AI Development ML 57

Marktechpost

SEPTEMBER 17, 2024

’ – Gideon Mendels (CEO at Comet) In conclusion, Opik is a powerful open-source tool that addresses many challenges developers face when working with LLMs. Opik ensures that LLM applications are reliable, accurate, and optimized for performance by providing both pre-deployment testing and post-deployment monitoring.

LLM 104

LLM Large Language Models Automation Data Scientist 104

Marktechpost

JULY 23, 2024

This self-directed data curation is essential for advancing AI reasoning capabilities promoting model independence and efficiency. The study highlights innovative model supervision’s role in AI development, particularly for AGI. If you like our work, you will love our newsletter.

Large Language Models 80

Large Language Models AI AI AI Developer 80

Marktechpost

SEPTEMBER 12, 2024

OpenAI has once again pushed the boundaries of AI with the release of OpenAI Strawberry o1 , a large language model (LLM) designed specifically for complex reasoning tasks. OpenAI o1 represents a significant leap in AI’s ability to reason, think critically, and improve performance through reinforcement learning.

OpenAI 113

OpenAI Large Language Models AI AI 113

Marktechpost

AUGUST 2, 2024

This methodology extends beyond safety applications, potentially benefiting various AI development domains. Sharing these resources with the research community aims to accelerate progress in AI safety and responsible deployment. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

LLM 104

LLM Large Language Models AI AI 104

Marktechpost

JULY 20, 2024

By teaching language models to combine informal reasoning with formal verification, Lean-STaR advances automated theorem proving, which is crucial for mathematics and AI development. Don’t Forget to join our 46k+ ML SubReddit Find Upcoming AI Webinars here The post How can Informal Reasoning Improve Formal Theorem Proving?

Automation 108

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ODSC - Open Data Science

MARCH 24, 2023

Microsoft’s Azure OpenAI Service Integrates ChatGPT for Advanced NLP and Responsible AI Microsoft has announced through a blog post that ChatGPT is now available in the Azure OpenAI Service. Topics include data Ingestion from object storage, dataset preparation (infer labels, splitting, augmenting, optimizing), and more.

Data Ingestion 52

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ODSC - Open Data Science

SEPTEMBER 12, 2024

Machine Learning and Data Science: Academia vs. Industry In this article, we compiled a list of the top five problems that every ML specialist faces only on the job, highlighting the gap between university curriculum and real-world practice. Ideal for anyone interested in machine learning, AI development, or data science careers.

Software Engineer 40

Software Engineer Data Science Machine Learning AI 40

TheSequence

OCTOBER 27, 2023

Consequently, companies are adopting a new AI development process that makes it possible to realize business value from AI much faster, and you can adopt it too. The Predibase platform allows developers to efficiently fine-tune and serve open source LLMs on scalable managed infrastructure with just a few lines of code.

AI 122

AI AI ChatGPT Machine Learning 122

Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. Where is LLMOps in DevOps and MLOps In MLOps, engineers are dedicated to enhancing the efficiency and impact of ML model deployment. Their mission?

Large Language Models 52

Large Language Models DevOps Prompt Engineer Prompt Engineering 52

Marktechpost

SEPTEMBER 19, 2024

These frameworks aim to address catastrophic risks associated with AI, including potential threats from chemical or biological weapons, cyberattacks, and loss of control. Each AI developer must establish their threshold, creating a diverse landscape of safety approaches. If you like our work, you will love our newsletter.

AI 57

AI AI OpenAI Artificial Intelligence 57

Snorkel AI

APRIL 16, 2024

Paroma Varma, co-founder at Snorkel AI, and Ali Arsenjani, director of AI/ML partner engineering at Google, discussed the role of data in the development and implementation of LLMs. He’s the director for AI and ML partner engineering at Google. PV: That’s exactly right.

Large Language Models 52

Large Language Models ML LLM Generative AI 52

ODSC - Open Data Science

OCTOBER 5, 2023

13 Companies Leading the Way in AI Development Let’s take a quick look at some of the companies that will be at the ODSC West AI Expo, what they do, and how they’re changing the AI landscape. Here’s how you can customize your ODSC West schedule with ease.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Artificial Intelligence 52

ODSC - Open Data Science

APRIL 27, 2023

5 Concerns for ML Safety in the Era of LLMs and Generative AI The growth of large language models and generative AI has spurred new concerns for ML safety and cybersecurity. 5 Data Engineering and Data Science Cloud Options for 2023 AI development is incredibly resource intensive.

ML 52

ML Data Science Large Language Models Machine Learning 52

Marktechpost

SEPTEMBER 14, 2024

Let’s explore the key aspects of the Nemotron-Mini-4B-Instruct, technical capabilities, application areas, and implications for AI developers and users. The company advises developers to use the recommended prompt templates to mitigate these risks, as the model may otherwise produce socially undesirable or inaccurate text.

Automation 117

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Marktechpost

AUGUST 29, 2024

It has partnered with leading companies in the AI industry, including Docker, LangChain, LlamaIndex, and Weights & Biases, to provide developers with the tools they need to build and deploy AI applications quickly and efficiently. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Generative AI 116

Generative AI Large Language Models AI AI 116

Marktechpost

JULY 22, 2024

By maintaining consistent hyperparameters and using cost-effective strategies like downsizing data pools and limiting training iterations, the researchers ensured an efficient and resource-conscious development process. The sandbox’s compatibility with existing model-centric infrastructures makes it a versatile tool for AI development.

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