Lifeboat Foundation

Ironically #AI has been proven to develop racial and gender bias. Gee, I wonder why?

For the second year in a row, more than a dozen AI researchers from African countries have been denied visas to a major AI conference in Canada.

Canada’s decision to refuse visas to African AI researchers seems ham-fisted, given that the country’s tech industry has been the beneficiary, in recent years, of America’s move toward isolationism. In 2017, Trudeau launched a visa program designed to attract high-tech workers—including those who found themselves unable to get into the US—by streamlining Canada’s visa-approval process. The recent decision to block access to NeurIPS for a diverse pool of talent appears to be a step in the opposite direction.

Continue reading “African AI Experts Get Excluded From a Conference—Again” »

If Goldman Sachs’ new tool launches through Marcus, a human-digital hybrid approach would be a wise choice.

Goldman Sachs created a market-ready robo advisor and is mulling how to launch it, Financial Planning reports. The automated platform will represent Goldman’s digital entry into the smaller investor market, per Rachel Schnoll — who recently became the head of Goldman’s FinLife CX RIA platform — as cited by Financial Planning. The new robo advisor may be built in part on algorithms that Goldman acquired from financial life management firm United Capital, when it acquired the company for $750 million in May.

The new robo advisor could be introduced to the market via Goldman’s Marcus segment — here’s why it would be a good match. Goldman could extend a portion of the personal touch it brings to its Private Wealth Management clients to Marcus clients by offering them financial advice via the new robo advisor.

Continue reading “Goldman Sachs has created a market-ready robo advisor” »

A UCLA research team has devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. The researchers use artificial intelligence to turn two-dimensional images into stacks of virtual three-dimensional slices showing activity inside organisms.

In a study published in Nature Methods, the scientists also reported that their framework, called “Deep-Z,” was able to fix errors or aberrations in images, such as when a sample is tilted or curved. Further, they demonstrated that the system could take 2-D images from one type of microscope and virtually create 3D images of the sample as if they were obtained by another, more advanced microscope.

Continue reading “Researchers convert 2-D images into 3D using deep learning” »

This smart waste bin uses AI to sort your recyclable trash automatically.

While many futures are generalists, there is a need for foresight professionals centered on specific fields, as well. Perhaps no area is more in need of innovative outlooks for the future than healthcare. With rising costs, aging populations and personnel shortages, the challenges are many. But so are the opportunities to employ emerging technologies. In the first part of a two part series, host Mark Sackler discusses these challenge with two nursing Ph.D.’s, Oriana Beaudet and Dan Pesut. Part One addresses the need for foresight both in nursing specifically and healthcare in general, as well as the global challenges of an aging population. Part two will drill down to individual ssues, including automation, robotics and artificial intelligence as caregiving tools for the future.

This two legged robot could change how search and rescue operations are handled, with the ablity to enter areas too dangerous for humans.

AMOLF researchers and their collaborators from the Advanced Science Research Center (ASRC/CUNY) in New York have created a nanostructured surface capable of performing on-the-fly mathematical operations on an input image. This discovery could boost the speed of existing imaging processing techniques and lower energy usage. The work enables ultrafast object detection and augmented reality applications. The researchers publish their results today in the journal Nano Letters.

Image processing is at the core of several rapidly growing technologies, such as augmented reality, autonomous driving and more general object recognition. But how does a computer find and recognize an object? The initial step is to understand where its boundaries are, hence edge detection in an image becomes the starting point for image recognition. Edge detection is typically performed digitally using integrated electronic circuits implying fundamental speed limitations and high energy consumption, or in an analog fashion which requires bulky optics.

Extremists could generate ‘synthetic propaganda’, automatically creating white supremacist screeds, researchers warn.

The problem is the largest-ever GPT-2 model can also be fine-tuned for propaganda by extremist groups.