The United States has the highest coronavirus cases in the world and with vaccine efforts underway, there is an urgency to find solutions by using AI and ML technologies.
Robot automation of COVID-19 tests in Spain enabled by AI is supporting as researchers collaborate to contain the outbreak in the US and around the world.
Psychologists agree that social isolation during the COVID-19 pandemic is creating mental health problems. Socialization is part of our human health and with the coronavirus grounding everybody, mental health risks will rise.
Smart speakers from AI are addressing this problem by offering social support for people including voice-messaging communication round the clock.
These and more insights on our weekly AI update
Global Race to Combat COVID-19 Crisis
When attempting to tackle the problem of potential coronavirus treatments the analytical prowess of the modern data ecosystem is especially limited. Companies with immense computing resources would attempt only to be expected to dedicate those resources in some way to the global effort to combat the virus¹.
These efforts are extremely valuable in some ways. For instance, you can apply the context-aware text analysis of Semantic Scholar to the thousands of articles on known coronaviruses to make them searchable by researchers around the globe.
AI and tech have made large advances in drug discovery. Companies have been on the promise of using AI to speed up the process by which new substances can be identified that may have an effect on a given condition.
Coronavirus is a natural target for some companies and research organizations touting early numbers: 10 or 100 such substances identified which may be effective against coronavirus. “An AI found 10 possible coronavirus cures”- the types of announcements that gather headlines around them.
It does not mean these applications of AI are bad, but rather that they belong to a set with few actionable outcomes.
AI searching for a COVID-19 Vaccine in the United States
The United States becomes the country with the greatest number of known COVID-19 cases in the world. It is going to be one of the biggest challenges for the United States to fight against this outbreak.
Health care workers are the heroes with inadequately supplied supplies on the frontlines, but the world’s scientific community is also considering how it can respond and provide solutions.
AI and data science experts are in demand right now as the world scrambles for ways to avert disaster.
Four robots are automating up to 80,000 COVID-19 tests a day in Spain and AI is part of the search for a coronavirus vaccine in the United States. Microsoft, together with top AI universities in the country, launched the C3.ai Digital Transformation Institute and issued a call for AI techniques to mitigate pandemic fallout², with up to $5.8 million in prizes.
Supercomputer companies and major cloud providers like AWS, Microsoft’s Azure, and Google Cloud Platform joined a consortium last weekend to ensure coronavirus researchers don’t encounter compute limitations.
Governments are increasing surveillance as a result of the coronavirus. Dr. Michael Ryan, executive director at WHO said surveillance is an offensive strategy to combat the coronavirus.
Challenges Facing AI
The greatest problems with artificial intelligence are not primarily technical, but rather how to achieve value from the technology. Technologies like natural language processing and deep learning are capable of providing considerable value to organizations. The challenges are with the deployment of AI³.
An MIT Sloan Management Review survey indicated that “7 out of 10 companies surveyed report minimal or no impact from AI so far”. Among the 90% of companies that have made some investment in AI, fewer than 2 out of 5 report business gains from AI in the past three years. This number improves to 3 out of 5 when we include companies that have made significant investments in AI. Even so, this means 40% of organizations making significant investments in AI do not report business gains from AI.
In NewVantage Partners 2019 Big Data and AI Executive survey, firms report ongoing interest and an active embrace of AI technologies and solutions, with 91.5% of firms reporting ongoing investment in AI. But only 14.6% of firms report that they have deployed AI capabilities into widespread production.
Perhaps, as a result, the percentage of respondents agreeing that their pace of investment in AI and #bigdata was accelerating and fell from 92% in 2018 to 52% in 2019.
Maximizing AI Opportunities and Ethical Issues
Artificial intelligence technologies aren’t any more limited only in big tech and digital platform players of this world. AI technologies are being utilized from manufacturing to energy, health care to government, in fact, all industries and sectors are experimenting with AI.
But we are still unknown about AI’s real, as opposed to potential, impact. Companies are yet far from bearing fruit, just developing use cases.
How can we exploit AI⁴ to the fullest by leveraging data, talent, and other resources? And how can we do it ethically and within the regulation?
MIT Technology Review Insights surveyed 1,004 senior executives in different sectors and regions of the world to understand how organizations are using AI today and planning to do so in the future.
These are the key findings of this research:
✅ AI deployment is widespread but will take time to scale.
✅ Change management and data challenges do most to hinder the scaling of AI.
✅ The top AI use cases today are in the areas of quality control, customer care, and cybersecurity.
✅Currently nascent, data sharing can magnify the impact of AI.
✅Early AI adopters are benefiting the most, but also have war stories.
How AI is Pinpointing Opportunity Zones
What’s the best way to determine the O-Zones with richer investment potential when it comes to investing in opportunity zones⁵? Is it the traditional figures and facts such as those from substantially out-of-date US Census data? Or would the better choice be alternative data sources, such as social media, street views, and cellular data?
Skyline AI⁹, the New York City and Tel Aviv-based artificial intelligence investment manager for commercial real estate suggests answers in its whitepaper entitled “The Map is Not the Territory: Discerning the True Opportunity Within Opportunity Zones,” Skyline AI identified considering these alternative data sources rather than traditional census data delivers clearer views of tracts’ potential opportunity.
4,981 tracts scored higher median household incomes, while only 1,977 suffered lower incomes from 2014 to 2017. The states showing the greatest decline: Louisiana, New Mexico, & Nevada. A handful of New York City and Washington D.C. tracts gave evidence of critical and bewildering anomalies.
The whitepaper’s authors noted “When we apply these new lenses to O-Zone tracts, we find lots of these positive indicators of sustained economic growth present in areas otherwise listed as troubled.”
AI Element of Kaizo
ADutch company called Kaizo¹⁰ uses AI and gamification to provide feedback on agents’ work, tips on what to do differently, and tools to set and work to goals — all of which can be used remotely, in the cloud.
It is announced $3 million in a seed round of funding co-led by Gradient — Google’s AI venture fund — and French VC Partech. Christoph Auer-Welsbach, a former partner at IBM Ventures, is joining Kaizo as a co-founder, alongside founder Dominik Blattner.
At the moment, customer service & the idea of gamification to motivate employees might feel like the last thing but it is actually timely in responding to people living with the coronavirus.
People are turning to the internet and remote services more as they are spending more time at home. These are driving a lot of traffic to sites and customer support centers are getting overwhelmed with queries. Customer support is an integral part of a company’s stability and growth that has embraced remote work to meet the demands of a globalized customer-base in the current time.
This is where the AI element of Kaizo steps in by taking on the need to proactively report into a system. Kaizo approaches applying AI to existing ticket data from platforms like Zendesk and Salesforce to optimize the customer support workflow.
Smart Speakers: AI curbing Loneliness in the midst of COVID-19 Lockdowns
Loneliness is a global problem that can be as bad for your health as smoking 15 cigarettes a day or being severely overweight according to scientists. People who are older than 70 will exacerbate the problem because of their self-isolation guidelines for coronavirus-related lockdowns in cities.
Professor Arlene Astell, a psychologist at the University of Reading says “Because humans are social beings, most people find not being able to engage in social interactions a negative experience,”
Astell believes smart speakers could prove to be an increasingly useful tool in the current climate, in which billions of pensioners around the world are in social isolation due to the risk of spreading coronavirus.
Smart speakers⁶guarantee an immediate opportunity to connect with a voice, no matter what time of day or night unlike phone and video calls, texts and emails — which remain highly recommended ways of keeping in touch during the coronavirus outbreak. The UK’s largest mental health charity, Mind cautiously welcomed the AI project.
Smart speakers, the champion AI tool recognizes that although some elderly people are fast-adopters, it will be a challenge to increase their use more widely. Other projects are testing the limits of AI as a potential tool to foster older residents.
Digital AI Research Conference switched to Video Conferencing
The details about one of the largest-ever all-digital AI research⁷ conferences is shared by the organizers of the International Conference on Learning Representations (ICLR).
ICLR will include live chat, live Zoom video calls for Q&As and research author meetings, and the ability to upvote questions or vote for speakers using Slido in the weeklong, online-only affair which will feature more than 650 machine learning works.
The conference will now take place entirely online because of the Covid19 pandemic which was previously scheduled to take place next month in Addis Ababa, Ethiopia. ICLR treats the cancellation as an opportunity to develop a model for remote conferences. ICLR will be rolled out across five time zones each day, and a video download option may be included for people with low bandwidth.
ICLR will feature Booths — spaces for active or passive participation in video chats with a host. Virtual Booths will be made for sponsors; a chosen list of invited speakers; workshops; and affinity groups like Women in MachineLearning, QueerinAI, and LatinXinAI. Additional details about the structure of workshops will be released in the weeks ahead.
Addressing Social Problems with AI
The founder, and chief executive of C3.ai (An artificial intelligence company) Thomas M. Siebel said: “The public-private consortium would spend $367 million in its initial five years, aiming its first awards at finding ways to slow the new coronavirus that is sweeping the globe.”
The C3.ai Digital Transformation Institute¹¹, the new research consortium includes commitments from Princeton, Carnegie Mellon, the Massachusetts Institute of Technology, the University of California, the University of Illinois and the University of Chicago, as well as C3.ai and Microsoft. It seeks to put top scientists onto gargantuan social problems with the help of AI — its first challenge being the pandemic.
The institute will speed up the development of medical treatments, designing and repurposing drugs, planning clinical trials, predicting the disease’s evolution, judging the value of interventions, improving public health strategies to fight infectious outbreaks.
A former U.S. secretary of state Condoleezza Rice, who serves on the C3.ai board and was recently named the next director of the Hoover Institution, a conservative think tank on the Stanford campus, called the initiative a unique opportunity to “better manage these phenomena and avert the worst outcomes for humanity.”
Adaptive Education Platform
There is an opportunity to design an intelligent, adaptive education⁸ platform with dramatic progress in machine-learning over the past decade. We can make education more effective, equitable and available to every child in the world with advances in artificial intelligence (AI).
The research established that students who receive personalized, 1:1 experience from human teachers outscore their peers on final exams.
Dr. Benjamin Bloom, the late educational psychologist, showed that students who receive personalized tutoring scorehigher than almost all of their fellow students who attendstandard classroom lectures.
We can build a computer-based tutor for millions of students around the world to establish adaptive education that represents a paradigm shift from the conventional model to an intelligent one. Each student is paired with a virtual “coach” in the adaptive model and the concept that can be scaled to millions of students at a fraction of the cost of human tutors.
Adaptive AI teaching performs three continuous functions:
Assessment: It can assess a learner’s knowledge
Targeted content: It makes personalized content, depending on the learner
Real-time interactions: It leverages the strategic use of AI at the full process level to make instructional decisions.
GANSynth: Adversarial Neural Audio Synthesis
Efficient audio synthesis is an inherently difficult machine-learning task, as human perception is sensitive to both global structure and fine-scale waveform coherence.
Autoregressive models, such as WaveNet, the model local structure at the expense of global latent structure and slow iterative sampling, while Generative Adversarial Networks (GANs), have global latent conditioning and efficient parallel sampling, but struggle to generate locally-coherent audio waveforms.
Through extensive empirical investigations on the NSynth Dataset, it is demonstrated that GANs are able to outperform strong WaveNet baselines on automated and human evaluation metrics, and efficiently generate audio several orders of magnitude faster than their autoregressive counterparts.
Using AI Tools to reduce Infrastructure Services Costs
AI tools and infrastructure services can be costly especially for models that target complex areas like medical research. But AI companies have stepped up by eliminating their fees:
NVIDIA¹² is offering a 90-days free license for Para bricks, which allows using AI for genomics purposes. The technology can significantly cut down the time for processing. It also features free support from Oracle Cloud Infrastructure and Core Scientific.
DataRobot¹³ is proving its platform without any charge. The technology allows the deployment, monitoring, and management of AI models at scale. The technology is also provided to the Kaggle competition.
Run: AI is providing its software for free to help with building virtualization layers for deep learning models.
DarwinAI¹³ has collaborated with the University of Waterloo’s VIP Lab to develop COVID-Net and is now making this technology open source. It is a convolutional neural network that detects COVID19 using chest radiography.
AI can help out make advanced drug discovery process can still be fast and effortless
For example, Gero Pte¹⁴ a startup using AI to accelerate drug development. It has used the technology to better isolate compounds for COVID-19 by testing treatments that are already used in humans.