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OpenAI's state-of-the-art machine vision AI is fooled by handwritten notes


Researchers from machine learning lab OpenAI have discovered that their state-of-the-art computer vision system can be deceived by tools no more sophisticated than a pen and a pad. As illustrated in the image above, simply writing down the name of an object and sticking it on another can be enough to trick the software into misidentifying what it sees. "We refer to these attacks as typographic attacks," write OpenAI's researchers in a blog post. "By exploiting the model's ability to read text robustly, we find that even photographs of hand-written text can often fool the model." They note that such attacks are similar to "adversarial images" that can fool commercial machine vision systems, but far simpler to produce.

Operationalizing AI – Introduction to the ModelOps Pipeline


Artificial Intelligence (AI) is all the buzz with everyone looking for ways to leverage AI in some capacity within their organization. Whether you're running a business focused on insurance, construction, or anything in between, the list of companies adding AI or Data Science teams to help their business succeed is growing every day. Unfortunately for those tasked with making the decision to fund these emerging teams, the ROI for AI investments isn't always immediately clear. Sure there are companies that have increased their bottom line by increasing their AI investment, however, their success isn't the norm. According to leading industry analysts it takes 9 months to turn an idea for an AI application into a mature, stable production capability, and that's assuming the idea isn't one of the 47% of AI investments that never make it out of the lab for one reason or another.

Startup Uses AI-Powered Garbage Bins to Monitor Pollution


In 2013, Peter Ceglinski and Andrew Turton set up their firm, Seabin, with a selfless ambition: "our ultimate goal is pretty simple. It's a world where sea bins are no longer needed for clean up," Ceglinski said, speaking at IBM Think Australia and New Zealand last month. As a report by ZDNet explains, the creators behind Seabin are focusing on building a future where their own product is only used for monitoring the sea, not for cleaning garbage. The cornerstone to this development is artificial intelligence (AI). "What started out as a garbage can has evolved into this global mission focused on data and behavioral change," Ceglinski said at IBM Think.

Building AI Leadership Brain Trust: Why Is Data Analytics Literacy Key To AI Competency Development?


This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO's to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO's to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog. Each of the blogs in this series explores either a group of skills or does a deeper dive into one of the skill areas. I have come to the conclusion that to unlock the last mile of AI value realization that board directors and CEOs must accelerate building a unified brain trust (a unified set of leadership skills that are hardwired in relevant digital and AI skills) to modernize their organizations more rapidly.

'Deep learning among top in-demand skills of 2020 in India' - Express Computer


Deep learning and data engineering are top nanodegree programmes showing the country's growing interest towards artificial intelligence (AI) and data, says a new report. According to a report by silicon-valley-based Udacity, Karnataka holds the lion's share for maximum nanodegree programmes in 2020. As much as 24 per cent demand for deep learning and 34 per cent of the total demand for data engineering nanodegree programmes comes from Karnataka, the company said in a statement. The demand for AI product manager (38 per cent) and product manager (60 per cent) is also the highest in the state. Data science and deep learning are the most popular nanodegree programmes in Maharashtra. More than 40 per cent of the enrollments come from this state.

Happy International Women's Day!


To celebrate International Women's Day, we take a look back over the past year of AIhub content and highlight some of our favourite articles, interviews, podcasts and videos, by, or featuring, women in the field. Falaah Arif Khan is an engineer/scientist by training and an artist by nature. She is currently Artist-in-Residence at the Center for Responsible AI at New York University. When we interviewed Falaah in 2020 she had just completed her first comic book, Meet AI. She has since teamed up with other AI researchers on other exciting projects.

Arlo's Video Doorbell and Pro 3 cameras helped me survive suburbia


Soon after moving to a house in the Atlanta metro area last year, I knew I needed a video doorbell. UPS and FedEx would often drop boxes off and never alert me (not great when package thieves are everywhere!). Plus, sales people had the gall to ring my doorbell, unmasked and oblivious to the global pandemic. And if I was playing with my toddler in the backyard or working in the basement, I had trouble hearing if someone was at my door. A video doorbell would solve all of those issues, and give my family a little peace of mind to boot.

The Playbook to Monitor Your Model's Performance in Production


As Machine Learning infrastructure has matured, the need for model monitoring has surged. Unfortunately this growing demand has not led to a foolproof playbook that explains to teams how to measure their model's performance. Performance analysis of production models can be complex, and every situation comes with its own set of challenges. Unfortunately, not every model application scenario has an obvious path to measuring performance like the toy problems that are taught in school. In this piece we will cover a number of challenges connected to availability of ground truth and discuss the performance metrics that are available to measure models in each scenario.

US government urged to 'jump start' smart cities - Cities Today - Connecting the world's urban leaders


The US federal government should do more to fund research and facilitate collaboration which helps cities tap the benefits of artificial intelligence (AI) and other emerging technologies, says a new report from non-profit thinktank the Information Technology and Innovation Foundation (ITIF). "Smart cities offer an important opportunity to address both infrastructure needs and strained state and local budgets at the same time," the report says, noting the large revenue shortfalls many cities face due to the pandemic. Cities can use AI in transport, the electrical grid, buildings, city operations and more. Similarly, a 2020 report from Microsoft and PwC found that AI-enabled decarbonisation technologies could reduce the carbon intensity of the global economy. ITIF's research outlines several key challenges to deployment.

Delivery startup Refraction AI raises $4.2M to expand service areas


Refraction AI, a company developing semi-autonomous delivery robots, today announced that it raised $4.2 million in seed funding led by Pillar VC. Refraction says that the proceeds will be used for customer acquisition, geographic expansion, and product development well into the next year. The worsening COVID-19 health crisis in much of the U.S. seems likely to hasten the adoption of self-guided robots and drones for goods transportation. They require disinfection, which companies like Kiwibot, Starship Technologies, and Postmates are conducting manually with sanitation teams. But in some cases, delivery rovers like Refraction's could minimize the risk of spreading disease.