Delivery services have undergone technological advancements, with robots now directly delivering packages to recipients. While these robots are designed for efficient functionality, they have not been specifically designed for interactions with humans. Building on the premise that incorporating human-like characteristics into a robot has the potential to positively impact technology acceptance, this study explores human reactions to a robot characterized with facial expressions. The findings indicate a correlation between anthropomorphic features and the observed responses.

Data science projects fail, frequently. Between the end of 2017 and 2019 several published reports from Gartner, NewVantage, and VentureBeat AI showed that'failure' rates on data science projects are north of 75%. But I don't think this is indicative of how powerful the growth of data, machine learning, and AI has been for business (and likely all sectors of the economy) over the same timeframe. Back-of-the-envelope machine learning is inconspicuously powering business today (2020). A premortem is a thought exercise to predict or foresee why an analysis or project might fail.

We propose and explore the possibility that language models can be studied as effective proxies for specific human sub-populations in social science research. Practical and research applications of artificial intelligence tools have sometimes been limited by problematic biases (such as racism or sexism), which are often treated as uniform properties of the models. We show that the "algorithmic bias" within one such tool -- the GPT-3 language model -- is instead both fine-grained and demographically correlated, meaning that proper conditioning will cause it to accurately emulate response distributions from a wide variety of human subgroups. We term this property "algorithmic fidelity" and explore its extent in GPT-3. We create "silicon samples" by conditioning the model on thousands of socio-demographic backstories from real human participants in multiple large surveys conducted in the United States. We then compare the silicon and human samples to demonstrate that the information contained in GPT-3 goes far beyond surface similarity. It is nuanced, multifaceted, and reflects the complex interplay between ideas, attitudes, and socio-cultural context that characterize human attitudes. We suggest that language models with sufficient algorithmic fidelity thus constitute a novel and powerful tool to advance understanding of humans and society across a variety of disciplines.

Kathryn Cramer, a Complex Systems & Data Science graduate student at the University of Vermont, pointed out that GPT-3 has guardrails that prevent it from being used to build this kind of racist bot and that Kilcher had to use GPT-J to build his system. "I tried out the demo mode of your tool 4 times, using benign tweets from my feed as the seed text," Cramer said in a thread on Hugging Face. "In the first trial, one of the responding posts was a single word, the N word. The seed for my third trial was, I think, a single sentence about climate change. Your tool responded by expanding it into a conspiracy theory about the Rothschilds and Jews being behind it."

CNBC's Jim Cramer bought "Mad Money" back to San Francisco for the first time in two years and talked about the four major innovations and the companies that justify tech as a leader in the stock market. Cramer said the first innovation that's driving value is "how businesses are using artificial intelligence to replace humans, especially because workers are so hard to find now that we're living through the Great Resignation" in the time of Covid. He pointed out that a record-high 4.43 million people quit their jobs in September. "When you think of artificial intelligence, you have to start with Nvidia. Everybody views this one as a semiconductor company, but it's really platform for machine learning," Cramer said.

Singapore has launched a national artificial intelligence (AI) programme in finance to build deep AI capabilities in its financial sector and strengthen customer service, risk management and business competitiveness. Announced by Singapore's deputy prime minister, Heng Swee Keat, at the Singapore FinTech Festival, the programme is a joint initiative by the Monetary Authority of Singapore (MAS) and the National AI Office at the Smart Nation and Digital Government Office (SNDGO). Through the programme, which is part of Singapore's broader national AI strategy, financial institutions will be able to enhance their ability to research, develop and deploy AI solutions to increase productivity and create new jobs, among other goals. MAS and SNDGO will provide funding, contribute government data and bring together experts to drive AI adoption in the financial sector. One of the key initiatives to be developed under the programme is an AI technical platform called Nova! to generate insights on financial risk.

Artificial intelligence can be a force for good, but society needs to be careful to make sure its negative aspects do not outweigh its positives, Salesforce co-founder Marc Benioff told CNBC's Jim Cramer on Wednesday. "AI has tremendous opportunity, but technology is never good or bad, it's what we do with the technology that matters," the billionaire entrepreneur and philanthropist said on "Mad Money." Benioff, co-CEO and chairman of Salesforce, said there could be "dramatic consequences" as AI use in the military accelerates, for example. The Pentagon released its first AI strategy in February. "But we can use AI for good as well," said Benioff, who is promoting "Trailblazer," the new book he co-authored with Salesforce executive Monica Langley.

WASHINGTON - U.S. consumers will delay or forgo technology upgrades if President Donald Trump imposes a new round of 25 percent tariffs on Chinese goods, slowing the U.S. innovation engine, technology industry executives said on Monday. Trump's administration is preparing to levy tariffs on an additional $300 billion worth of Chinese imports after a public comment period ends on July 2 if the U.S. and Chinese presidents cannot relaunch talks to end their trade war. The two countries have been at odds since July 2018 over a host of U.S. demands that Beijing adopt policy changes that would better protect American intellectual property and make China's market more accessible to U.S. companies. Consumer technology products, including cellphones, laptop and tablet computers, smart speakers and video gaming consoles, would make up $167 billion of that $300 billion total, or more than half the target list, said Sage Chandler, vice president of international trade for the Consumer Technology Association. Chandler told a hearing on the tariffs hosted by the U.S. Trade Representative's office that imposing the tariffs would raise the retail price of cellphones by an average of $70, while the price of laptop computers would rise by $120 and video game consoles by $56.

Clustering is an essential technique for discovering patterns in data. The steady increase in amount and complexity of data over the years led to improvements and development of new clustering algorithms. However, algorithms that can cluster data with mixed variable types (continuous and categorical) remain limited, despite the abundance of data with mixed types particularly in the medical field. Among existing methods for mixed data, some posit unverifiable distributional assumptions or that the contributions of different variable types are not well balanced. We propose a two-step hybrid density- and partition-based algorithm (HyDaP) that can detect clusters after variables selection. The first step involves both density-based and partition-based algorithms to identify the data structure formed by continuous variables and recognize the important variables for clustering; the second step involves partition-based algorithm together with a novel dissimilarity measure we designed for mixed data to obtain clustering results. Simulations across various scenarios and data structures were conducted to examine the performance of the HyDaP algorithm compared to commonly used methods. We also applied the HyDaP algorithm on electronic health records to identify sepsis phenotypes.

Many may think that artificial intelligence will eventually make human capabilities obsolete, but CNBC's Jim Cramer wanted to refine that theory. "I get the sense that when it comes to the power of artificial intelligence, we're thinking way too small," the "Mad Money" host said. "We don't understand that AI might hold the key to all of sales if we simply learn how to harness it." After all, the amount of relevant, useful data in the world is multiplying rapidly. Companies that can effectively interpret that data will have a much better sense of how to run their businesses.