Disclosures: This article expresses the opinions of the author, and is not to be taken as advice to purchase from nor invest in the companies mentioned. My firm, Cambrian AI Research, is fortunate to have many, if not most, semiconductor firms as our clients, including NVIDIA, Intel, IBM, Qualcomm, Blaize, Graphcore, Synopsys and Tenstorrent. We have no investment positions in any of the companies mentioned in this article. For more information, please visit our website at https://cambrian-AI.com.

The pandemic that has raged across the globe over the past year has shone a cold, hard light on many things--the varied levels of preparedness to respond; collective attitudes toward health, technology, and science; and vast financial and social inequities. As the world continues to navigate the covid-19 health crisis, and some places even begin a gradual return to work, school, travel, and recreation, it's critical to resolve the competing priorities of protecting the public's health equitably while ensuring privacy. The extended crisis has led to rapid change in work and social behavior, as well as an increased reliance on technology. The expanded and rapid adoption of artificial intelligence (AI) demonstrates how adaptive technologies are prone to intersect with humans and social institutions in potentially risky or inequitable ways. "Our relationship with technology as a whole will have shifted dramatically post-pandemic," says Yoav Schlesinger, principal of the ethical AI practice at Salesforce.

COVID-19 has undoubtedly accelerated the application of AI in the healthcare industry, such as virus surveillance, diagnosis, and patient risk assessments. AI-powered robots and digital assistants with real-time monitoring and analysis have enabled doctors to provide more effective and personalized treatment. Machine learning is the study of computer algorithms that improve automatically through experience. It is seen as a part of artificial intelligence. It gives algorithms the ability to "learn" from training data so as to identify patterns and make decisions with little human intervention.

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It took a global pandemic and stay-at-home orders for 1.5 billion people worldwide, but something is finally occurring to us: The future we thought we expected may not be the one we get. We know that things will change; how they'll change is a mystery. To envision a future altered by coronavirus, Quartz asked dozens of experts for their best predictions on how the world will be different in five years. Below is an answer from Zia Khan, the senior vice president of innovation at The Rockefeller Foundation, a private foundation that seeks to promote humanity's wellbeing. Many of his professional experiences--as a management consultant, serving on the World Economic Forum Advisory Council for Social Innovation--have helped show him how to use data and technology to positively transform people's lives.

Today, the practical synergies between economics and computer science are flourishing. We outline some of the many opportunities for the two disciplines to engage more deeply through the new MIT Schwarzman College of Computing." Nancy L. Rose is the Charles P. Kindleberger Professor of Applied Economics and head of the MIT Department of Economics, where her research and teaching focus on industrial organization, competition policy, and the economics of regulation. David Autor is the Ford Professor of Economics and co-director of the MIT Task Force on the Work of the Future. His scholarship explores the labor market impacts of technological change and globalization, earnings inequality, and disability insurance and labor supply.

Forecast, a Denmark-based startup that has developed "AI-powered" project management software, has raised $5.5 million in new funding. The round is led by Crane Venture Partners, with participation from existing backers SEED Capital and Heartcore. Forecast has raised $10 million in total funding to date. Founded in late 2016, Forecast describes itself as an AI-powered project management solution that automates manual project management tasks, and brings extra visibility and predictive capabilities to to project management. The idea is to help increase collaboration across teams with a better workflow and to improve planning.

Huge shortages, astronomical salaries, raids on engineering departments at universities--this has been the state of the job market for AI and machine learning experts for the past few years. And with AI technology finding use in new industries almost daily, it seemed demand for AI and machine learning expertise would never slack. Job search site Indeed looked for the answer to that question in its annual review of AI job postings. And Indeed concluded that it just might be seeing a slowdown--that is, if you call 29 percent growth a slowdown. The number of AI jobs listed on the site from May 2018 to May 2019 increased by 29 percent over the same period a year earlier.

Conversational experiences: Advances in natural language processing (NLP) enable people to have increasingly conversational experiences with computers through text and voice. Current implementations are rudimentary, but as platforms grow more capable and marketers onboard more of their own data, individual conversations based on customer context will be delivered at scale. Real-time personalization: Context, intent and journey stage are extracted from interactions to inform the delivery of tailored content, offers and promotions using propensity modeling, machine learning, machine vision and NLP. Identity resolution: Machine learning algorithms help sift through and map billions of ad impressions and hundreds of millions of device identifiers to provide marketers with greater confidence that the right message reaches the right person. Marketing orchestration: As AI takes on more campaign orchestration duties, the construct of the campaign dialogue or journey management workboard, where marketing specialists connect different triggers, channels and content, may become obsolete.

More than two years after Facebook started copying Snapchat's Stories feature, Snap has a new plan to get its Stories in more places. The company is bringing its Stories to third-party apps like Tinder and Houseparty as it deepens its relationship with outside developers. Snap announced the move at its Partner Summit in Los Angeles Thursday. The update, which comes with the expansion of Snap's developer platform, allows app makers to place Snapchat Stories inside their own apps with a new API called App Stories. With Tinder, one of the first apps to get the feature, this means you can send snaps directly from Snapchat to the dating app, where prospective matches can check out your story.