Connect with us


Half of unvaccinated workers say they’d rather quit than get vaccinated



California News Times

Does the obligation to be vaccinated at work push some employees to resign instead of being shot?

For example, a hospital in Lowville, NY The maternity ward had to be closed when dozens of staff left their jobs instead of getting vaccinated. Indiana University Health has at least 125 employees Has quit after refusing to be vaccinated.

Half of unvaccinated workers say they’d rather quit than get vaccinated Source link Half of unvaccinated workers say they’d rather quit than get vaccinated

Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *


Artificial intelligence is smart, but doesn’t it work well with others



California News Times

Studies have shown that humans find AI to be a frustrating teammate when playing cooperative games together and a challenge for “team intelligence”.

When it comes to games like chess and go, Artificial Intelligence (AI) programs far outperform the best players in the world. These “superhuman” AIs are unmatched competitors, but perhaps more difficult than competing with humans is to work with them. Can the same technology get along with people?

In a new study MIT Lincoln Laboratory researchers use advanced AI models that are well trained to play with teammates they have never met before, and how humans play collaborative card games fireworks. I looked for what I could do. In the single-blind experiment, participants played two sets of games. One used an AI agent as a teammate and the other used a rules-based agent, a bot manually programmed to play in a predefined way.

The results surprised the researchers. Not only did AI teammates perform worse than rule-based agents, humans have always hated playing with AI teammates. They found him to be unpredictable, unreliable, unreliable and felt negative even when the team gave a good score. An article detailing this study was accepted by the 2021 Neural Information Processing Systems (NeurIPS) Conference.

Fireworks experience

When playing the “Fireworks” cooperative card game, humans were dissatisfied and confused by the movements of their AI teammates. Credit: Bryan Mastergeorge

“This highlights the subtle difference between creating an AI that works objectively well and creating an AI that is subjectively reliable or prioritized,” the article co-wrote. Said Ross Allen, researcher in the artificial intelligence technology group. “They’re so close to each other that they can appear to be out of the sun, but this study showed that they’re actually two separate issues. We have to work to untangle them. “

Humans who dislike AI teammates may worry researchers who design this technology in collaboration with humans about real-world challenges such as missile protection and performing complex surgeries. This dynamic, called team intelligence, is the next frontier in AI research and uses a specific type of AI called reinforcement learning.

Reinforcement learning The AI ​​is not informed of the action to be taken, but by experimenting with the scenario several times, it discovers which action provides the most digital “reward”. It is this technology that has created superhuman chess and go players. Unlike rule-based algorithms, these AIs are not programmed to follow “if / then” instructions. This is because the results of human tasks you plan to work on, such as driving a car, are too high to be coded.

“Reinforcement learning is a much more versatile way to develop AI. If you can train him to learn to play chess, that agent isn’t necessarily going to drive a car. But with the right data, you can use the same algorithm to train another officer to drive a car, ”says Allen. “Theoretically, the sky is the limit of what it can do.”

Bad advice, bad game

Today, researchers are testing the performance of reinforcement learning models developed for collaboration in the same way that chess has served as a benchmark for testing competitive AI for decades. I use fireworks to do this.

The fireworks game is similar to the multiplayer format of Solitaire. Players work together to stack cards of the same suit in order. However, players cannot see their cards, only cards held by their teammates. Each player has severe restrictions on what can be communicated to their teammates, allowing them to choose the best card in their hand and then crush it.

Lincoln Laboratory researchers did not develop the AI ​​or the rules-based agent used in this experiment. Both agents are the best in their respective fields of fireworks performance. real, the AI ​​model was previously paired with an AI teammate who never played with them, the team achieved the highest score ever in a fireworks display between two unknown AI agents .

“It was a big result,” says Allen. “I thought if these AIs that I had never met before could come together and play really well, I should be able to bring in people who know how to play AI as well. They are also doing very well. That’s why I thought the AI ​​team could play well objectively, and I thought humans like it because, in general, if it works, they like things better. “

None of these expectations were met. Objectively, there was no statistical difference in scores between AI and rule-based agents. Subjectively, all 29 participants reported a clear preference for rule-based teammates in the survey. Participants were not told which agent and what game they were playing.

“One participant said he actually had a headache because he was stressed out by the AI ​​agent’s bad game,” said Jaimepena, researcher and author of the AI ​​Technology and Group article. Systems. “Another said rule-based agents thought they were ridiculous but achievable, but AI agents showed they understood the rules, but the movement was the look of the team. didn’t fit. For them, it gave a bad clue and played badly. “

Inhuman creativity

This perception that AI is “playing badly” is linked to the surprising behavior previously observed in reinforcement learning tasks. For example, when DeepMind’s AlphaGo first beat one of the best Go players in the world in 2016, one of the most admired moves made by AlphaGo was move 37 in game 2 An Unusual Move That The Human commentators thought it was a mistake. Subsequent analysis revealed that this move was actually very well calculated and described as a “genius”.

Such moves can be praised when performed by an AI opponent, but less likely to be celebrated in a team setting. Researchers at the Lincoln Laboratory have discovered that weird or seemingly illogical moves are the worst criminals for breaking human trust in the AI ​​teammates of these tightly coupled teams. Such movements not only reduce the player’s perception of how the player and their AI teammates work together, but also the amount of AI used, especially when the potential rewards are not immediately apparent. I also lowered what I wanted to do.

“There have been a lot of comments about giving up, like ‘I hate to handle this’,” said Hosea Siu, author of the article and researcher in the Autonomy and Control Systems Engineering group. Add.

Participants who rated themselves as fireworks experts, led by the majority of players in this survey, often abandoned AI players. Siu sees this as a concern for AI developers, as the main users of this technology are likely experts in the field.

“Let’s say you train a super intelligent AI guidance assistant for a missile defense scenario. You don’t give it to an intern. You give it to your expert on your ship who has been doing this for 25 years. Therefore, if there is a strong expert bias against it in the game scenario, it can manifest itself in actual operations, ”he adds.

Squeeze the human

The researchers say the AI ​​used in this study was not developed for human taste. But that’s part of the problem – not much. Like most collaborative AI models, this model is designed to score as high as possible, and its success is measured by its objective performance.

If the researchers don’t focus on the question of subjective human tastes, “you can’t create the AI ​​that humans really want to use,” says Allen. “It’s easier to work with AI which improves very sharp numbers. It is much more difficult to work on an AI that works in this favorite world of the humans of Musier. “

Solving this more difficult problem is the goal of the MeRLin (Mission-Ready Reinforcement Learning) project. The experiment was funded by the technical office of MIT Lincoln Laboratory in conjunction with the U.S. Air Force’s Artificial Intelligence Accelerator and MIT’s Electrical and Computer Engineering Division. Chemistry. This project investigates what keeps collaborative AI technology from leaping out of the play space and into more delicate reality.

Researchers believe that AI’s ability to explain its behavior builds trust. This will be the focus of their work next year.

“I can imagine we would repeat the experiment, but after the fact – and it’s not as easy as it looks – the humans said, ‘I don’t understand why you made that move. Did you do that? “If the AI ​​can give some insight into what they think is going to happen based on their behavior, our guess is that humans ‘oh, weird thought, but I get it now.’ Trust it. Even if you don’t change basic AI decisions, the results will change completely, “Allen says.

Like post-game chats, this type of exchange often helps humans form friendships and cooperate as a team.

“It may also be a staff prejudice. Most AI teams don’t want to tackle these squeaky people and their limp issues, ”Siu adds with a laugh. “People want to do math and optimization. This is the basis, but it is not enough.

Mastering fireworks-like games between AI and humans has the potential to open up a world of possibilities for teaming up with intelligence in the future. But the technology can remain mechanical or human until researchers can bridge the gap between AI performance and human taste.

Reference: Ho Chit Siu, Jaime D. Pena, Kimberlee C. Chang, Edenna Chen, Yutai Zhou, Victor J. Lopez, Kyle Palko, RossE “Human AI Team Assessment for Rule-Based Agents Learned to Hanabi “”. Allen, accepts, 2021 Neural Information Processing Systems (NeurIPS) Conference..
arXiv: 2107.07630

Artificial Intelligence Is Smart, But Doesn’t Work Well With Others Source Link Artificial Intelligence Is Smart, But Doesn’t Work Well With Others

Continue Reading


Ventures Platform and Hustle Fund back Nigerian fintech Brass in $ 1.7 million round – TechCrunch



California News Times

SMEs represent over 95% of all Nigerian businesses. However, despite their size and importance, most of them are underserved by financial institutions and lack the full range of financial services needed to expand their operations.

Aside from complete financial needs including credit and small business Obligatory Other important resources to understand their financial operations.

Brass is a Nigerian fintech that addresses these challenges by providing banking services to small businesses. The company has secured $ 1.7 million in funding to expand its services to “local entrepreneurs, traders and fast growing businesses.”

Sora Akindle When Emmanuel Okeke Brass was created in July 2020. Before Brass, CEO Akindolu Kudi’s product manager, backed by YC, and CTO Okeke were CTO of Paystack, a Stripe subsidiary.

Akindle’s work at Kudi has focused on the issues facing SMEs in Nigeria...He said these companies pay sellers, transfer funds and Globally Company health.

But why start with brass when you have an existing product in the Nigerian market that can be used by small businesses and entrepreneurs? Shining For example, we offer both personal and business banking services (priority is given to the latter).. Neobank for carbon consumers When Hisada Has different stages of providing business functions to SMEs.. Pro Spa, a company supported by YC, I don’t want to think of myself as an online bank, so I also offer software and banking services to micro-businesses and the self-employed.

Akindolu believes that while these products have an entry point into the SME market, they do not meet the overall needs of banks in companies like Brass.

“There are a lot of ways that money can flow out of the business, like payroll, vendor payments, invoicing, and so on. We want to support the cash flow of a business. We support them in these areas and the money is flowing. We want to keep going and allow them to keep growing their business, ”Akindle said of Brass’s app. “That’s what we do most of the time in Brass today. We support our financial operations and our treasury... “

Brass was wrapped up in a professional bank account, which included credit and payment services, payroll and expense management, API support, cash flow analysis, team and contact management, point of sale. sales, debit cards, credit cards and other basic business services. We offer a series of products. ..

Among all these characteristics, Brass makes a big bet on the achievements of Brass Capital. This space is already heating up on other platforms such as: float Provides working capital and software services to businesses. That said, Brass Capital has seen great success in a short period of time. Cash Flow Finance Services claims that 20 Brass private beta clients paid more than $ 2 million in credit after using it for six months.

Akindolu told TechCrunch that the company will be opening the service to the public soon...

According to Brass, many customers use the platform as their default currency trading service provider... FinTech makes money by offering credits and API calls in its regular product offering, the CEO said...

From schools and shopping centers to restaurants and fintechs like Eden and Mono that use complete banking solutions, we have more than 5,000 customers. And youLike any other platform, Brass seeks to simultaneously optimize the platform for different levels of activity with different needs.

“What we’re trying to do is build a financial services stack. We may be overkill for small business. They may find us unnecessary, so I’m more interested in SMEs. “

According to founder and general partner Kola Aina, the mission of making banking services for SMEs work was one of the reasons pan-African venture capital firm Ventures Platform invested in the business.

Other investors include Flutterwave CEO Olugbenga “GB” Agboola, Paystack co-founder Ezra Olubi, the Hustle fund, Acuity Ventures and the hedged fund.

Previous supporters include Olumide Soyombo Capital Voltron, Leonard Stiegler and Fola Olatunji-David.

“we Excited Support the Sora and Brass teams, which provide important financial technology to businesses in Africa, including Nigeria In regards to “41.5 million businesses,” said Elizabeth Inn, general partner of Hustle Fund.

it’s not Nevertheless In Nigeria, access to full banking services remains one of the most important constraints for SMEs and is the largest economy in Africa. Indeed, the formal SME sector on the continent has an annual financing gap. $ 136 billion Although they represent over 80% of employed people.

For this reason, Akindolu has confirmed that Brass will use part of its funds to expand into Kenya and South Africa by next year (the former has been incorporated). Key to promoting expansion plans across Africa Flutterwave, the one-year-old company said in a statement. Brass also plans to diversify its customer base by launching more product categories, including a focus on credit. This market.

Ventures Platform, Hustle Fund back Nigerian fintech Brass in $ 1.7 million round – TechCrunch Source link Ventures Platform, Hustle Fund back Nigerian fintech Brass in $ 1.7 million round – TechCrunch

Continue Reading


Kitchenful meal planner startup raises $ 1.9 million from VentureFriends, Goodwater Capital and Jabbar – TechCrunch



California News Times

With the pandemic making us delivery specialists, consumers have switched to in-car meal kits, given the combination of delivery and home cooking. However, many diet kits can be rigid.

German startup Kitchenful made this possible, allowing users to browse recipes from food bloggers and create personalized meal plans that can be tailored to their tastes and dietary needs. Another product from Kitchen Full is that it tries to be just as affordable. I wrote earlier this year ..

After successfully completing the Y-Combinator Summer 2021 program, we raised $ 1.9 million in fundraising from VentureFriends, Goodwater Capital and the Jabbar Internet Group.

Former investors include Y-Combinator, Valentin Stalf (co-founder and CEO of N26), Samih Toukan (co-founder of Souq), David Fischer (HighSnobiety), Maik Ludewig (DurstExpress MD) and Victor Henning. (Co-founder of Mendeley).

Co-founders Chris Schiller and Christian Hartung are currently planning to expand into the EU and North America.

Schiller previously spent four years as vice president of products at HelloFresh, and he and Hartung were previously on Rocket Internet.

Schiller said: “We believe that cooking at home should be simple, enjoyable and personal. But in today’s world, “what is dinner? Is always a nerve-racking and grocery question. Shopping takes the time and energy of millions of people every day. We are correcting this with new services and the ambition to become the # 1 home cooking brand in the United States and Europe. “

Apostolos Apostolakis, co-founder and partner of Venture Friends, said: With very relevant experience with its founder, Kitchenful is in a promising position to become a leading home cooking brand. “

Kitchen Full may encounter strong opposition from other new players in this Lollipop space etc …

Meal Planner Startup Kitchenful Raises $ 1.9 Million from VentureFriends, Goodwater Capital and Jabbar – TechCrunch Source Link Meal Planner Startup Kitchenful Raises $ 1.9 Million from VentureFriends, Goodwater Capital and Jabbar – TechCrunch

Continue Reading


Ad Blocker Detected!

Please Disable Adblocker to Continue, We are able to fund this blog only with the Ads Revenue, Thanks!