Our team of experts is ready to answer!
You can contact us directly
Telegram iconFacebook messenger iconWhatApp icon
Fill in the form below and you will receive an answer within 2 working days.
Or fill in the form below and you will receive an answer within 2 working days.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Reading Time
5 Minutes
Anzhella Pankratova
Content Author at OpenCV.ai
AI Weekly Insights: NVIDIA's Grace Hopper & More

Digest 1 | OpenCV AI Weekly Insights

What happened in the AI world this week? Let's find out! From groundbreaking headlines to jaw-dropping breakthroughs, we've got the scoop.
August 14, 2023

Welcome to the OpenCV AI Weekly Insights Digest!

Our aim is to keep you up to date with the latest news and developments in the world of Artificial Intelligence. Whether you're an experienced AI enthusiast or just starting to explore the world of AI — our digest is designed to keep you informed and inspired 🔥

Ready to dive into this week's AI adventures? Let's explore the exciting updates that are transforming the world of AI!

NVIDIA Announces Grace Hopper with 282 GB VRAM

NVIDIA has announced GH200, which combines the Grace Hopper Superchip with HBM3E memory technology to enhance the performance of supercomputing applications for Generative AI. It increases AI inference speed by 1.2 times and training speed by 1.7 times compared to the A100 Tensor Core GPU.

NVIDIA highlights GH200's technical capabilities, specifically its ability to handle complex AI workloads, simulations, and scientific computations. The exceptional bandwidth and capacity of HBM3E memory technology allow smooth data transfer and manipulation, which improves the efficiency of compute-intensive tasks.

The base version has 141 GB VRAM and 72 ARM Neoverse cores with 480 GB LPDDR5X RAM. You can combine dual "superchips" using NVIDIA NVLink to get 480x2 GB of fast memory (RAM).

The commercial release is scheduled for the second quarter of 2024. Keep an eye out for updates!

Source:  NVIDIA News Article

Pioneering Antibody Discovery Through AI-Driven Innovation

LabGenius is pioneering a transformative AI-powered approach to engineering new medical antibodies. Creating medical antibodies has traditionally been a long process of selecting amino acid combinations and testing them.

LabGenius uses AI to quickly analyze biological data and find strong antibody candidates with great accuracy — the process involves the AI model assessing 700 initial options from a pool of 100,000 antibodies and then automating the design, construction, and testing of these candidates to find promising leads for further exploration.

This approach could revolutionize drug discovery and streamline a historically complicated process. LabGenius promises to improve patient care with better and safer antibody treatments. They do this by discovering molecules that other methods might miss and using these discoveries to create better outcomes for patients. This will lead to a new era of medical innovation!

Source:  Wired Article

Navigating the Bias Labyrinth: Political Biases in Large Language Models

In the age of AI, Large Language Models have been found to contain political biases. This was revealed in a groundbreaking expose by MIT Technology Review, raising concerns about the impartiality of AI as we approach technological evolution.

The article explores how AI Large Language Models, which are designed to generate text like humans, can be biased like humans. Researchers have found that these models often reflect the same biases and tendencies present in human communication.

The researchers tested 14 popular models and discovered that OpenAI's ChatGPT and GPT-4 leaned towards the left when it came to libertarianism, while Meta's LLaMA leaned towards the right when it came to authoritarianism.

Large Language Models are utilized in various industries to enhance products and services and provide better user experiences. Millions of people rely on these models daily, which highlights the importance of building them without political biases. Failing to do so could result in unintended consequences that may cause harm to users.

To avoid issues, companies must proactively identify and address potential biases in their AI models. This involves incorporating diverse perspectives and ensuring that the data used to train the models is representative of the real world. By doing so, companies can create more ethical and fair AI models that benefit everyone.

Source:  MIT Technology Review Article

Disney Forms AI Exploration Team to Drive Cost-Efficiency Initiatives

In a bid to enhance operational efficiency and drive cost reduction, entertainment giant Disney has established a specialized team dedicated to harnessing the capabilities of Artificial Intelligence (AI). This group will delve into creative approaches for seamlessly integrating AI across different aspects of Disney's operations.

The task force will focus on investigating how AI can streamline operations, automate repetitive tasks, and identify areas where cost savings can be realized across Disney's diverse range of endeavors, including film production, theme parks, and media networks. It will be fascinating to see what specific AI technologies and strategies Disney uses to achieve its objectives!

Source:  Reuters Article

Transforming Coding Landscape with Generative AI

Stability.AI has introduced the StableCode LLM, a new technology that could change how coding works. They explained all the details of the technology and how it could change the coding world in a recent blog post.

By learning from existing code, StableCode LLM can create code snippets, algorithms, and even entire software modules automatically, making development faster and more efficient. It can handle complicated programming languages and patterns.

Stability.AI believes that humans and AI can work together to achieve better results. They designed StableCode LLM to help developers instead of replacing them. With the help of StableCode LLM, developers can unlock their full potential and achieve greater success in their work.

Source:  Stability.AI Blog

Thanks for joining us in this edition of OpenCV AI Weekly Insights Digest. We're thrilled to be your AI news source, and we're eager to share the latest gems with you!

So, buckle up and get ready to dive into the AI universe. Stay tuned for more! Your weekly dose of AI knowledge is just a scroll away.

See you in the next edition!

Let's discuss your project

Book a complimentary consultation

Read also

April 12, 2024

Digest 19 | OpenCV AI Weekly Insights

Dive into the latest OpenCV AI Weekly Insights Digest for concise updates on computer vision and AI. Explore OpenCV's distribution for Android, iPhone LiDAR depth estimation, simplified GPT-2 model training by Andrej Karpathy, and Apple's ReALM system, promising enhanced AI interactions.
April 11, 2024

OpenCV For Android Distribution

The OpenCV.ai team, creators of the essential OpenCV library for computer vision, has launched version 4.9.0 in partnership with ARM Holdings. This update is a big step for Android developers, simplifying how OpenCV is used in Android apps and boosting performance on ARM devices.
April 4, 2024

Depth estimation Technology in Iphones

The article examines the iPhone's LiDAR technology, detailing its use in depth measurement for improved photography, augmented reality, and navigation. Through experiments, it highlights how LiDAR contributes to more engaging digital experiences by accurately mapping environments.