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AI-powered ecommerce recommendation engine Constructor nabs $55M

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The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Constructor, a San Francisco, California-based ecommerce personalization startup, today announced that it raised $55 million in a series A round led by Silversmith Capital Partners. The funding, which brings the company's total raised to $61.5 million, will be put toward product development, hiring, and go-to-market efforts, according to CEO Eli Finkelshteyn. Online commerce conversions are well behind in-store -- the average online shop sees less than 3% in conversions. But even though $4.2 trillion was spent on ecommerce platforms in 2020 alone, few ecommerce retailers have invested in a digital merchandising strategy.


Money and mind control: Big Tech slams ethics brakes on AI

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SAN FRANCISCO (REUTERS) - In September last year, Google's cloud unit looked into using artificial intelligence (AI) to help a financial firm decide whom to lend money to. It turned down the client's idea after weeks of internal discussions, deeming the project too ethically dicey because the AI technology could perpetuate biases like those around race and gender. Since early last year, Google has also blocked new AI features analysing emotions, fearing cultural insensitivity, while Microsoft restricted software mimicking voices and IBM rejected a client request for an advanced facial-recognition system. All these technologies were curbed by panels of executives or other leaders, according to interviews with AI ethics chiefs at the three US technology giants. Reported here for the first time, their vetoes and the deliberations that led to them reflect a nascent industry-wide drive to balance the pursuit of lucrative AI systems with a greater consideration of social responsibility.


Tesla rolls out Full Self Driving 10 beta with more confident decision making

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If Tesla's last big Full Self Driving beta was about enabling more semi-autonomous features off the highway, its newest release is focused more on helping you trust those features. Electrek notes Tesla has started rolling out a Full Self Driving 10 beta that, from early reports, appears to make smarter and more confident decisions off the highway. It won't necessarily "blow your mind," as Elon Musk claimed, but it appears to deliver smoother turns, roundabouts and merges. One driver found that it finally navigated San Francisco's twisty Lombard Street without requiring intervention. Users have also noticed improved visuals.


Tesla rolls out Full Self Driving 10 beta with more confident decision making

Engadget

If Tesla's last big Full Self Driving beta was about enabling more semi-autonomous features off the highway, its newest release is focused more on helping you trust those features. Electrek notes Tesla has started rolling out a Full Self Driving 10 beta that, from early reports, appears to make smarter and more confident decisions off the highway. It won't necessarily "blow your mind," as Elon Musk claimed, but it appears to deliver smoother turns, roundabouts and merges. One driver found that it finally navigated San Francisco's twisty Lombard Street without requiring intervention. Users have also noticed improved visuals.


Region's AI sector has potential according to think tank

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An IBM researcher holds a silicon wafer with embedded IBM Telum chips designed to maximize artificial intelligence capabilities. The chips were developed at Albany Nanotech and made in partnership with Samsung. The Albany area was recent cited by the Brookings Institution for having the potential to create an AI sector. ALBANY -- The Capital Region is one of 87 "potential adoption centers" in the United States for companies and researchers focused on the use of artificial intelligence, or AI, according to a new report from the Brookings Institution, a left-leaning think tank. The San Francisco Bay area is No. 1 in AI, while other upstate cities, Buffalo, Rochester and Syracuse, were also listed as potential adoption centers.


In the US, the AI Industry Risks Becoming Winner-Take-Most

WIRED

A new study warns that the American AI industry is highly concentrated in the San Francisco Bay Area and that this could prove to be a weakness in the long run. The Bay leads all other regions of the country in AI research and investment activity, accounting for about one-quarter of AI conference papers, patents, and companies in the US. Bay Area metro areas see levels of AI activity four times higher than other top cities for AI development. "When you have a high percentage of all AI activity in Bay Area metros, you may be overconcentrating, losing diversity, and getting groupthink in the algorithmic economy. It locks in a winner-take-most dimension to this sector, and that's where we hope that federal policy will begin to invest in new and different AI clusters in new and different places to provide a balance or counter," Mark Muro, policy director at the Brookings Institution and the study's coauthor, told WIRED.


AI algorithm to treat psychiatric illness, stroke developed by Google, Mayo teams

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San Francisco: Google is all set to collaborate with researchers to develop new artificial intelligence (AI) algorithms to improve brain stimulation devices to treat people with psychiatric illness and direct brain injuries, such as stroke. The tech giant has tied up with researchers at Mayo Clinic to develop a set of paradigms, or viewpoints, that simplify comparisons between effects of electrical stimulation on the brain. They developed a new type of algorithm called "Basis Profile Curve Identification". "Our findings show that this new type of algorithm may help us understand which brain regions directly interact with one another, which in turn may help guide placement of electrodes for stimulating devices to treat network brain diseases," said Kai Miller, a Mayo Clinic neurosurgeon. "As new technology emerges, this type of algorithm may help us to better treat patients with epilepsy, movement disorders like Parkinson's disease, and psychiatric illnesses like obsessive-compulsive disorder and depression," he added.


Artificial Intelligence at Square - Two Use-Cases

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Megan serves as Publishing Operations Manager at Emerj, and is currently attending The American University in Paris, where she is pursuing degrees in global communications and international business administration. Square is a financial services company that aims to "build common business tools in unconventional ways so more people can start, run and grow their businesses." Founded in 2009 in San Francisco by Twitter Co-Founder Jack Dorsey and Jim McKelvey, Square reports total net revenue of $9.5 billion for 2020. Originally known for its card-reader dongles, Square has expanded to create a business toolkit for small business owners, including various hardware and software products and services such as Square Capital, Square Terminal, and most recently, Square Banking. We will begin by taking a closer look at how Square uses machine learning to enable its various software solutions that aim to increase fraud protection for sellers.


The Thoughts The Civilized Keep

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GPT-3 is the latest attempt by OpenAI, a tech research lab in San Francisco, to unlock artificial intelligence with an anvil rather than a hairpin. As brute force strategies go, the results are impressive. The language-generating model performs well across a striking range of contexts. Given only simple prompts, GPT-3 writes not just interesting short stories and clever songs, but also executable code such as web graphics. GPT-3's ability to dazzle with prose and poetry that appears entirely natural, even erudite or lyrical, is less surprising. It's a parlor trick that its predecessor performed a year earlier, though its then-massive 1.5 billion parameters are swamped by GPT-3's power, which uses 175 billion parameters to enhance its stylistic abstractions and semantic associations. Just like their great-grandmother, Joseph Weizenbaum's ELIZA, a natural language processing program developed in the 1960s, these systems benefit considerably from human reliance on familiar heuristics for speakers' cognitive abilities.