Interviews with technical leaders, investors, and business executives about the impact AI is having on business models, markets, products, and consumer behavior. Read More
Monthly Archives: February 2021
GPT-3 Demo Showcase & Examples
Get inspired and discover how companies are implementing the OpenAI GPT-3 API to power new use cases
Generative Pre-trained Transformer 3 (GPT-3) is OpenAI’s third-generation language prediction model, whose output is often difficult to distinguish from that written by a human. On this site, you can discover some of the best APIs and SaaS products to integrate with applications. Read More
Most People Can’t Tell the Difference Between Art Made by Humans and by AI, a Rather Concerning New Study Says
“There is a battle rising between humans and machines.”
No, that’s not a voiceover from another Matrix or Terminator movie. That’s the first line of a new study on how humans perceive artworks made by computers versus those made by humans, and, according to the findings, published in the journal Empirical Studies in the Arts, things don’t look great for the humans.
When the researcher Harsha Gangadharbatla saw the headlines three years ago about a painting created via artificial intelligence by the collective Obvious selling for $432,500 at Christie’s, he didn’t just shake his head at the price. He wondered what this might teach us about how humans perceive art. Read More
GCHQ: Pioneering a New National Security — The Ethics of Artificial Intelligence
…AI is now present in every aspect of British life. It enables our telecommunications systems, our smartphones, our banks, our National Health Service. The UK’s global leadership in AI and data science is a major part of what has made the UK a thriving cyber power, and AI stands to add billions to the British economy.
… At GCHQ, we believe that AI capabilities will be at the heart of our future ability to protect the UK. They will enable analysts to manage the ever-increasing volume and complexity of data, improving the quality and speed of their decision-making. Keeping the UK’s citizens safe and prosperous in a digital age will increasingly depend on the success of these systems.
…These are major issues of international importance and this paper can only hope to begin a conversation on the way ahead. Read More
VinVL: Making Visual Representations Matter in Vision-Language Models
This paper presents a detailed study of improving visual representations for vision language (VL)tasks and develops an improved object detection model to provide object-centric representations of images. Compared to the most widely used bottom-up and top-down model [2], the new model is bigger,better-designed for VL tasks, and pre-trained on much larger training corpora that combine multiple public annotated object detection datasets. Therefore, it can generate representations of a richer collection of visual objects and concepts. While previous VL research focuses mainly on improving the vision-language fusion model and leaves the object detection model improvement untouched, we show that visual features matter significantly in VL models. In our experiments we feed the visual features generated by the new object detection model into a Transformer-based VL fusion model OSCAR[21],and utilize an improved approach OSCAR+ to pre-train the VL model and fine-tune it on a wide range of downstream VL tasks. Our results show that the new visual features significantly improve the performance across all VL tasks, creating new state-of-the-art results on seven public benchmarks. We will release the new object detection model to public. Read More
This is how we lost control of our faces
The largest ever study of facial-recognition data shows how much the rise of deep learning has fueled a loss of privacy.
In 1964, mathematician and computer scientist Woodrow Bledsoe first attempted the task of matching suspects’ faces to mugshots. He measured out the distances between different facial features in printed photographs and fed them into a computer program. His rudimentary successes would set off decades of research into teaching machines to recognize human faces.
Now a new study shows just how much this enterprise has eroded our privacy. It hasn’t just fueled an increasingly powerful tool of surveillance. The latest generation of deep-learning-based facial recognition has completely disrupted our norms of consent. Read More
13 Common Mistakes That Can Derail Your AI Initiatives
13 experts from Forbes Technology Council share common mistakes to watch out for when implementing AI.
- Adopting Too Many Tools At Once
- Not Having A Clear Objective
- Not Having A Single Source Of Truth
- Not Analyzing Enough Data
- Incorrectly Structuring Datasets
- Implementing Siloed Solutions
- Not Having The Right Size Team
- Not Doing The Necessary Groundwork
- Assuming AI Is A Catch-All Solution
- Misidentifying Both The Problem And The Best Solution
- Implementing AI For Its Own Sake
- Implementing Solutions Without Sufficient Data
- Thinking AI Is ‘One-Size-Fits-All’
U.S. Holds Slim Edge over China in Artificial Intelligence, Former Google Chairman Says
The chairman of a special commission on artificial intelligence warned Congress the United States is only one to two years ahead of China in developing artificial intelligence, as Beijing remains “relentlessly focused” on achieving dominance across the broad spectrum of high technologies.
Testifying Tuesday before the Senate Armed Services Committee, Eric Schmidt, former chairman of Google, said the United States needs to maintain a five to 10-year advantage over its “pacing competitor” in AI and other high technology fields like quantum computing. Read More
Band of AI startups launch ‘rebel alliance’ for interoperability
More than 20 AI startups have banded together to create the AI Infrastructure Alliance in order to build a software and hardware stack for machine learning and adopt common standards. The alliance brings together companies like Algorithmia; Determined AI, which works with deep learning; data monitoring startup WhyLabs; and Pachyderm, a data science company that raised $16 million last year in a round led by M12, formerly Microsoft Ventures. A spokesperson for the alliance said partner organizations have raised about $200 million in funding from investors.
Dan Jeffries, chief tech evangelist at Pachyderm, will serve as director of the alliance. He said the group began to form from conversations that started over a year ago. Participants include a number of companies whose founders have experience running systems at scale within Big Tech companies. For example, WhyLabs CEO and cofounder Alessya Visnjic worked on fixing machine learning issues at Amazon, and Jeffries previously worked with machine learning at Red Hat. Read More
China Develops Monkey Facial Recognition Using AI Technology
A research team from China’s Northwest University is using artificial intelligence (AI) and other new technologies to develop a facial recognition technology for monkey to identify thousands of Sichuan golden snub-nosed monkeys in the Qinling Mountain in Shaanxi Province.
Similar to the current facial recognition technology, the technology for monkey can extract the facial feature information of the monkey to establish the identity database of the individual monkey in Qinling Mountains, the Xinhua News Agency reported.
“When monkey facial recognition technology is fully developed, we can integrate the technology into an infrared camera sets in the mountains. The system will automatically recognize the monkeys, name them and analyze their behavior,” said Zhang He, a member of the Northwest University research team. Read More
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