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Thanksgiving generates $5.3 billion in revenue, and Black Friday 2022 saw record-breaking e-commerce sales of $9.12 billion

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This year’s online holiday shopping season is expected to be subdued, according to analysts and e-commerce leaders. Sales in the first three weeks of November were essentially flat compared to the same period last year because of a weaker economy, inflation, and an increase in people returning to traditional in-store shopping in the wake of the Covid-19 pandemic. However, on the surface, the long Thanksgiving weekend appears to be more prosperous than anticipated, even though development has undoubtedly slowed this year after the spike during the pandemic.

According to data from Adobe Analytics, Black Friday sales surpassed $9 billion for the first time yesterday, with online sales totaling $9.12 billion. This represents a record for the day, an increase of 2.3% over sales from a year ago, and is also somewhat higher than what Adobe had anticipated before the day. Adobe doesn’t break out volumes in its report, making it difficult to determine whether the higher numbers are attributable to more purchases or simply higher prices this year owing to inflation.

For those assessing how the e-commerce market and consumer confidence are faring during what is the most significant and significant time for shopping in the year, Black Friday is a primary focus.

Salesforce releases its own statistics based on 1.5 billion shoppers, and it said that at 5 p.m. ET on Black Friday, online sales had hit $8 billion in the United States and $40 billion globally, with the most heavily discounted products being luxury handbags, clothing, and home appliances.

According to Rob Garf, VP & GM of retail at Salesforce, “Our data shows such a strong association between discount rates and online sales as buyers hung on for the biggest and best offers.” “Consumers on a tight budget are looking for value and pricing. And on Black Friday, stores responded by offering the biggest holiday discounts.

According to Adobe, the most popular categories for customers looking for deals and discounts on Black Friday were toys, video games, and consumer electronics.

Thanksgiving Day’s results were also better than expected: On Thursday, consumers spent $5.29 billion online. This is higher than the $5.1 billion that Adobe had originally predicted for the day and is up 2.9% from a year ago. According to Salesforce, worldwide online sales increased 1% on Thanksgiving to $31 billion, while domestically they increased 9% to $7.5 billion. Furthermore, according to Salesforce, mobile devices accounted for 78% of sales traffic. It claimed that the average order value was $105 globally and $120 for sales in the United States.

With the growth of e-commerce, “Christmas shopping” has undergone a significant change. Online shopping has expanded not only the days and hours that people can shop, but it has also expanded and muddled the idea of seasonality in “holiday” shopping. Black Friday, the day following Thanksgiving, used to be the “first day” of holiday shopping, but that tradition was abandoned years ago when deals began on Thursday.

Of course, it has also had an effect on how people shop. An ever-increasing part of that is being played by mobile devices. On Black Friday, smartphones accounted for a record 48% of total e-commerce transactions (up from 44% in 2021). Thanksgiving remains a stronger day for mobile sales, in part due to the fact that customers are not in stores or at their computers (they are spending time with friends and family, not at their offices!). Thursday saw a 5.5% increase in online transactions made through mobile devices compared to a year ago.

According to Vivek Pandya, chief analyst at Adobe Digital Insights, “mobile shopping had struggled to develop for many years as customers found the experience insufficient compared to desktop.” Thanksgiving this year marked an important turning point, demonstrating how much these encounters have advanced thanks to smartphones.

Additionally, the use of buy-now-pay-later services is increasing, a sign that both customers need to utilize this method and that it is becoming a more common alternative to credit. BNPL orders increased 78% on Black Friday, and according to sales data, they are up 81% from the same day a week prior. Notably, there is a significant increase over the day before as well. Buy-now-pay-later sales and orders increased by 1.3% and 0.7%, respectively, on Thanksgiving (indicating more of it being used for bigger-ticket items). Everything is great as long as there are no longer manageable bills down the road.

According to Adobe, it tracks sales for about 100 million SKUs and 18 different product categories across approximately 1 trillion visits to U.S. retail websites. It claims that 85% of the largest online retailers in the United States utilize it, and its analytics will contain anonymised data from some of its consumers. It stated that since November 1st, around $77.74 billion has been spent online.

The bigger question may actually be whether the increase in activity seen on Thanksgiving will be sustained through the rest of Cyber Week, which includes today’s Black Friday, Cyber Monday, and the weekend in between, as well as the rest of the days and weeks leading up to the New Year. Salesforce and Adobe may have different numbers and measurement parameters, but both are seeing growth. Overall, Adobe forecasts that this year’s Cyber Week will bring in $34.8 billion in online purchases, up 2.8% from the $33.9 billion the previous year.

The Cyber Week of 2021 was actually 1.4% lower than the Cyber Week of 2020, therefore this is a change.

In order to put those numbers into perspective, the National Retail Federation forecasts holiday sales growth of 6% to 8%, while Digital Commerce 360 predicts growth of 6.1% for the time period.

Whatever the case, it’s possible that sales won’t continue in full or even in the near future. According to Adobe, sales for today, often known as Black Friday, are likely to reach $9 billion, an increase of just 1% from 2021 figures.

For a few reasons, it’s crucial to monitor the holiday shopping season. First off, it is typically the busiest sales time of the year for retailers, with the potential to make or break the entire year. (For this reason, Amazon’s stock fell by about 20% following its most recent earnings, which saw the company slash its sales guidance and issue a warning about lower-than-expected holiday spending.)

Due to their disproportionate significance, Christmas sales data from online retailers can be used to predict the health of the e-commerce sector as a whole.

But there are some signs that choppy waters lie ahead if growth is what we’re chasing. According to Adobe, online sales in the first three weeks of November were steady at $64.59 billion, representing a 0.1% increase over 2021.

This is in contrast to physical retailers becoming more assertive in regaining their audience. The U.S. National Retail Federation predicted that 166.3 million people will shop over the long weekend.

Although there is a lot of speculation over how inflation will affect consumer behavior, our research indicates that this Thanksgiving holiday weekend will see strong store visitation and a record number of customers taking advantage of value pricing, according to NRF President and CEO Matthew Shay. “Retailers are ready to meet consumers wherever they want to shop with great products at prices they want to pay, and we are optimistic that retail sales will remain robust in the weeks ahead.”

More sales statistics updates will be posted when they become available.

As Editor here at GeekReply, I'm a big fan of all things Geeky. Most of my contributions to the site are technology related, but I'm also a big fan of video games. My genres of choice include RPGs, MMOs, Grand Strategy, and Simulation. If I'm not chasing after the latest gear on my MMO of choice, I'm here at GeekReply reporting on the latest in Geek culture.

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A group of humanoid robots from Agility will take care of your spanx

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So far, the humanoid robotics business has only been full of promises and test runs. These programs only use a few robots and don’t usually lead to anything more important, but they are important for the eventual use of new technology. While a pilot with logistics giant GXO went well, Agility announced on Thursday that it has now signed a formal deal.

Moving plastic totes around a Spanx factory in Georgia will be Digit’s first job, and that’s not a lie. The number of two-legged robots that will be taking boxes off of cobots and putting them on conveyor belts has not been made public, so it is likely that it is still too low. When it comes to tens or hundreds of thousands, most people would be happy to share that information.

They are leased as part of a model called “robots-as-a-service” instead of being bought outright. This way, the client can put off paying the huge upfront costs of such a complicated system while still getting support and software updates.

Last year, GXO started to test drive Digit robots. A pilot deal was just announced between the logistics company and Apptronik, one of Agility’s biggest rivals. I’m not sure how one will change the other.

When Peggy Johnson became CEO of Agility in March, she made it clear that the company was focused on ROI. This is a big change in a field where results are still mostly theoretical.

Johnson said, “There will be many firsts in the humanoid robot market in the years to come, but I’m very proud of the fact that Agility is the first company to have real humanoid robots deployed at a customer site, making money and solving real-world business problems.” “Agility has always been focused on the only metric that matters: giving our customers value by putting Digit to work. This milestone deployment sets a new standard for the whole industry.”

It’s not a surprise that Agility, based in Oregon, was the first to reach another important milestone. The company has been ahead of the rest of the market in terms of development and deployment. Of course, the industry is still very new, and there isn’t a clear market leader yet.

Amazon started testing Agility systems in its own warehouses in October of last year, but neither company has said what will happen next.

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Zuckerberg says that competitors with closed-source AI are trying to “make God”

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In an interview that came out Thursday, Mark Zuckerberg, CEO of Meta, talked about his hopes for the future of AI. He said that he strongly believes there will not be “just one AI.” While talking about how open source can help many people get AI tools, Zuckerberg took a moment to criticize the work of competitors who he didn’t name because he thinks they aren’t being open. He said that these competitors seem to think they are “creating God.”

In a new YouTube interview with Kane Sutter (@Kallaway), Zuckerberg said, “I don’t think that AI technology should be kind of hoarded and… that one company gets to use it to build whatever central, single product that they’re building.”

“It really turns me off when tech people talk about making this ‘one true AI,'” he said. He said, “It’s almost like they think they’re making God or something, but that’s not what we’re doing.” “That’s not how I see this going.”

“I see why, if you’re in an AI lab.” You want to think that what you’re doing is really important, right? It sounds like, “We’re making the one real thing for the future.” But, you know, in real life, that’s not how things work, right?” Zuckerberg talked about it. “It’s not like everyone has just one app on their phone that they use.” Not everyone wants all of their content to come from the same person. People don’t want to buy everything from just one store.

During the talk, Zuckerberg said that many different AIs should be made to capture people’s wide range of interests. On Thursday, the company also announced early tests of its AI Studio software in the U.S. This software will let creators and other people make AI avatars that can message people on Instagram. The AIs will be able to chat with people and answer questions from their followers in a fun way. To avoid confusion, they will be marked as “AI.”

As an example, the CEO of Meta said he didn’t think companies that build closed AI platforms were making the best experiences for people.

He went on, “You want to unlock and…unlock as many people as possible to try new things.” “Well, that’s what culture is, right?” Nobody is letting one group of people tell everyone what to do.

His comments sound a bit like he’s upset because they came out soon after news that Meta had tried to talk to Apple about putting its AIs into Apple’s operating systems instead of just working with OpenAI at launch but was turned down. Bloomberg says that Apple decided not to have formal talks with Meta because it didn’t think Meta’s privacy policies were strong enough.

Without a deal, Meta will not be able to reach the billions of iPhone users that there could be in the world. It looks like Meta’s plan B is to make technology that can be used for more than just smartphones.

During the interview, Zuckerberg talked about the progress the company is making with the Ray-Ban Meta smart glasses. He said that one day, this progress would meet up with the work that is already being done on full holographic displays. But he said the first one will be more popular in the short term.

He said, “I actually think you can have a great experience with cameras, a microphone, speakers, and the ability to do multimodal AI.” This was before the glasses had any kind of display. It also costs less because it doesn’t have a screen. The Meta Quest Pro costs $1,000, while Meta’s smart glasses cost around $300.

Before convergence, Zuckerberg said there would be three different kinds of products: smart glasses without screens, displays that show information on the top of the head, and full holographic displays. He said that one day, people might not have neural interfaces connected to their brains but instead wear a wristband that picks up signals from the brain and lets their hand talk to it. This would let them talk to the neural interface with their hand, which is barely moving. In time, it might also let people type.

Zuckerberg did warn that these kinds of inputs and AI experiences might not be able to replace smartphones right away. “I don’t think that in the history of technology, the new platform has ever made people stop using the old one completely.” “You just don’t use it as much,” he said.

People do things on their phones now that they might have done on their computers 10 to 15 years ago.

He said, “I think that will also happen with glasses.” “We’re not going to give up our phones.” You’ll just keep it in your pocket and only pull it out when you need to use it. But I think more and more people will just say, “Hey, I can take this picture with my glasses on.” The CEO said, “I can ask AI this question or send someone a message; it’s just a lot easier with glasses.”

The speaker said, “I wouldn’t be surprised if, in 10 years, we still have phones, but we’ll probably use them in a much more deliberate way instead of just grabbing them for any technological task we want to do.”

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What a new study says suggests that ChatGPT may have passed the Turing test

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René Descartes, a French philosopher who may or may not have been high on pot, had an interesting thought in 1637: can a machine think? Alan Turing, an English mathematician and computer scientist, gave the answer to this 300-year-old question in 1950: “Who cares?” He said a better question was what would become known as the “Turing test”: if there was a person, a machine, and a human interrogator, could the machine ever trick the human interrogator into thinking it was the person?

Turing changed the question in this way 74 years ago. Now, researchers at the University of California, San Diego, think they have the answer. A new study that had people talk to either different AI systems or another person for five minutes suggests that the answer might be “yes.”

“After a five-minute conversation, participants in our experiment were no better than random at identifying GPT-4. According to the preprint paper, which has not yet undergone peer review, this suggests that current AI systems can deceive people into believing they are human. “These results probably set a lower bound on how likely it is that someone will lie in more naturalistic settings, where people may not be aware of the possibility of lying or only focus on finding it.”

Even though this is a big event that makes headlines, it’s not a milestone that everyone agrees on. The researchers say that Turing first thought of the imitation game as a way to test intelligence, but “many objections have been raised to this idea.” People, for example, are known for being able to humanize almost anything. We want to connect with things, whether they’re people, dogs, or a Roomba with googly eyes on top of it.

Also, it’s interesting that ChatGPT-4 and ChatGPT-3.5, which was also tested, only persuaded humans that it was a person about half of the time, which isn’t much better than random chance. What does this result really mean?

As it turns out, ELIZA was one of the AI systems that the team built into the experiment as a backup plan. She was made at MIT in the mid-1960s and was one of the first programs of her kind. She was impressive for her time, but she doesn’t have much to do with modern large-language model-based systems or LLM-based systems.

“ELIZA could only give pre-written answers, which greatly limited what it could do. Live Science talked to Nell Watson, an AI researcher at the Institute of Electrical and Electronics Engineers (IEEE), about how it might fool someone for five minutes but soon show its flaws. “Language models are completely adaptable; they can put together answers to a lot of different topics, speak in specific languages or sociolects, and show who they are by displaying personality and values that are based on their characters.” a significant improvement over something that a person, no matter how intelligent and careful they were, programmed by hand.

She was perfect for the experiment because she was the same as everyone else. How do you explain test subjects who are lazy and pick between “human” and “machine” at random? If ELIZA gets the same score as chance, then the test is probably not being taken seriously because she’s not that good. In what way can you tell how much of the effect is just people giving things human traits? How much did ELIZA get them to change their minds? That much is probably how much it is.

In fact, ELIZA got only 22%, which is just over 1 in 5 people believing she was human. It’s more likely that ChatGPT has passed the Turing test now that test subjects could reliably tell the difference between some computers and people, but not ChatGPT, the researchers write.

So, does this mean we’re entering a new era of AI that acts like humans? Are computers smarter than people now? Maybe, but we probably shouldn’t make our decisions too quickly.

The researchers say, “In the end, it seems unlikely that the Turing test provides either necessary or sufficient evidence for intelligence. At best, it provides probabilistic support.” The people who took part weren’t even looking for what you might call “intelligence”; the paper says they “were more focused on linguistic style and socio-emotional factors than more traditional notions of intelligence such as knowledge and reasoning.” This “could reflect interrogators’ latent assumption that social intelligence has become the human trait that is most difficult for machines to copy.”

Which brings up a scary question: is the fall of humans the bigger problem than the rise of machines?

“Real humans were actually more successful, convincing interrogators that they were human two-thirds of the time,” the paper’s co-author, Cameron Jones, told Tech Xplore. “Our results suggest that in the real world, people might not be able to reliably tell if they’re talking to a human or an AI system.”

“In the real world, people might not be as aware that they’re talking to an AI system, so the rate of lying might be even higher,” he warned. “This makes me wonder what AI systems will be used for in the future, whether they are used to do bots, do customer service jobs, or spread fake news or fraud.”

There is a draft of the study on arXiv, but it has not yet been reviewed by other scientists.

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