Getty Images released Generative AI by iStock, an affordable image generation service trained on their licensed data, providing designers with a text-to-image tool. Powered by NVIDIA Picasso, it offers legal protection, advanced editing features, and the ability to create images at up to 4K resolution.
The AI revolution returns to gamers and content creators with lifelike characters and new GPUs, as NVIDIA takes center stage at CES. NVIDIA introduces generative AI models for digital avatars and announces partnerships with major developers.
Data scientists often overlook the importance of communication. Avoid using technical jargon and instead explain complex concepts in everyday language. Use real-world examples to make abstract ideas more understandable.
AWS customers in healthcare, finance, and public sectors can now extract valuable insights from documents stored in Amazon S3 using AWS intelligent document processing (IDP) with AI services like Amazon Textract. Two solutions are provided: a Python script for quick processing and a turnkey deployment using AWS CDK for a resilient and flexible IDP pipeline.
NVIDIA Studio debuts powerful software and hardware upgrades at CES, including new GeForce RTX 40 SUPER Series GPUs and NVIDIA Studio laptops from top brands. The launch also introduces Generative AI by iStock from Getty Images and RTX Video HDR for enhanced content creation and video quality.
LLMs suffer from inaccuracies at scale, hindering enterprise adoption of generative AI. Despite the risks, the transformative potential of generative AI is clear, and organizations must prioritize their data foundation to integrate it effectively.
In 2024, data teams are facing a new reality of being ROI-driven and efficient, with funding and growth declining significantly in recent years. To navigate this, data professionals should seek feedback from stakeholders and address areas for improvement in order to align with business value.
Midjourney launched alpha version of image synthesis model, Midjourney v6, with fans noting more detail and a different approach to prompting. Critics still bristle about the controversial practice of training models using human-made artwork obtained without permission.
ChatGPT, a large language model, has made significant progress in tool use and reasoning, with researchers equipping it with external tools like code interpreters and search engines, as well as exploring its internal reasoning capacities. The surge in language model papers in 2023 reflects the community's interest and the potential for practical applications.
Wipro's collaboration with AWS helps organizations overcome challenges in managing isolated data science solutions, offering automation, scalability, and model quality. By implementing Amazon SageMaker, Wipro addresses collaboration, scalability, MLOps, and reusability challenges for its customers.
In the early '00s, Geoff Hinton introduced the contrastive divergence algorithm, allowing the training of the restricted Boltzmann machine. Harmoniums, or restricted Boltzmann machines, are neural networks operating on binary data, with visible and hidden units, and are useful for modeling discrete data.
Microsoft's Orca-2 LLM is a significant development, showcasing the possibility of creating effective, small, fine-tuned language models. The use of synthetic training data generated by other LLMs is a fascinating concept with significant implications for the future.
Spain's second-biggest mobile operator, Orange España, experienced a major outage due to a security breach where an unknown party obtained a weak password and accessed an account managing the company's internet traffic. The breach occurred when the party logged into Orange's RIPE NCC account using the password "ripeadmin."
Generative AI has unlocked potential in AI, including text generation and code generation. One area evolving is using NLP to generate SQL queries, making data analysis more accessible to non-technical users.
GenAI is in high demand, but building a model that drives business value is challenging. Quick integrations won't cut it, and differentiation is key. High-quality proprietary data is the GenAI differentiator for success.