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Reckitt/Mead Johnson Nutrition voluntarily recalls select batches of Nutramigen Hypoallergenic Infant Formula Powder because of possible health risk

  • All product tested by MJN was confirmed negative for contaminants.
  • No illnesses or adverse consumer reactions have been reported to date.
  • No Nutramigen liquid formulas or any other Reckitt nutrition products are impacted.

 

 

PARSIPPANY, N.J. — (BUSINESS WIRE) — Reckitt/Mead Johnson Nutrition (MJN), a producer of nutrition products, announced today that it has voluntarily chosen to recall from the U.S. market select batches of Nutramigen Powder, a specialty infant formula for the dietary management of Cows Milk Allergy (CMA) in 12.6 and 19.8 oz cans, due to a possibility of contamination with Cronobacter sakazakii in product sampled outside the U.S. All product in question went through extensive testing by MJN and tested negative for the bacteria.


Cronobacter bacteria can cause severe, life-threatening infections (sepsis) or meningitis (an inflammation of the membranes that protect the brain and spine). Symptoms of sepsis and meningitis may include poor feeding, irritability, temperature changes, jaundice (yellow skin and whites of the eyes), grunting breaths and abnormal movements. Cronobacter infection may also cause bowel damage and may spread through the blood to other parts of the body.

 

Nutramigen in 12.6 and 19.8 oz containers was manufactured in June 2023 and distributed primarily in June, July, and August 2023. Based on the limited availability of the remaining stock of this special infant formula, it is believed that much, if not all, of the products recalled in the United States have been consumed. There are no reports of illnesses or adverse events to date. The products were distributed through retail stores nationwide. The batches in question can be identified by the batch code on the bottom of the can.

 

The following recalled product batch codes and can size associated with each batch were distributed in the U.S.:

  • ZL3FHG (12.6 oz cans);
  • ZL3FMH (12.6 oz cans);
  • ZL3FPE (12.6 oz cans);
  • ZL3FQD (12.6 oz cans);
  • ZL3FRW (19.8 oz cans); and
  • ZL3FXJ (12.6 oz cans).

 

The products have a UPC Code of 300871239418 or 300871239456 and “Use By Date” of “1 Jan 2025”.

 

No other U.S. distributed Nutramigen batches or other Reckitt products are impacted

Reckitt/Mead Johnson Nutrition manufactured additional products during this finished product campaign and distributed them outside of the U.S. Reckitt/Mead Johnson Nutrition will be contacting the regulatory authorities in each of those countries to determine the proper disposition of those products.

 

If parents have any questions, they should consult with their pediatrician or contact us at 866-534-9986 24/7 or by email at consumer.relations@rb.com

 

We are committed to the highest level of quality and safety and it is for this reason that we have taken this measure. Other testing of the batches in question tested negative for Cronobacter and other bacteria.

 

The health and safety of infants is our highest priority. All of our products undergo rigorous and industry-leading quality tests and checks to ensure that they meet or exceed all standards set by regulatory bodies, including the World Health Organization and the U.S. Food and Drug Administration. It is for this reason that we have confidence in the safety and quality of every infant formula we make.

 

What Consumers Should Do if They Purchased This Product

Consumers who purchased Nutramigen should check the bottom of the can to identify whether the batch number is affected. Product with the batch codes listed above should be disposed of, or contact us for a total refund. Please contact us at 866-534-9986 or by email at consumer.relations@rb.com and we will help verify if this product was impacted. If you have any concerns, contact your health care provider. For more information, please visit us at www.enfamil.com.

Contacts

Media Contact: US.CA.MEDIAandPR@reckitt.com

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Amazon Prime Video plans to start showing ads on Jan. 29, with option for customers to pay extra $2.99 per month for no ads

Movies and TV shows on Amazon’s streaming service will start getting broken up with ads in January — unless you’re willing to pony up an extra fee each month.

 

 

Chris Welch / The Verge:

 

 

—  Earlier this year, Amazon announced plans to start incorporating ads into movies and TV shows streamed from its Prime Video service, and now the company has revealed a specific date when you’ll start seeing them: it’s January 29th.

 

“This will allow us to continue investing in compelling content and keep increasing that investment over a long period of time,” the company said in an email to customers about the pending shift to “limited advertisements.”

 

“We aim to have meaningfully fewer ads than linear TV and other streaming TV providers. No action is required from you, and there is no change to the current price of your Prime membership,” the company wrote. Customers have the option of paying an additional $2.99 per month to keep avoiding advertisements.

 

The rest of the email summarizes the many benefits of a Prime subscription — no doubt an attempt to keep customers from canceling over this decision. Verge readers were none too pleased about the initial news back in September:

 

Amazon Prime currently costs $14.99 each month or $139 annually. (Prime Video can be subscribed to individually for $8.99/month.) The new charge for ad-free streaming would bring Prime to just under $18, and would push standalone Prime Video to just under $12.

 

Amazon also operates Freevee, a free, ad-sponsored streaming service. The company’s email notes that “live event content such as sports, and content offered through Amazon Freevee will continue to include advertising.”

 

The move comes as competing streaming services continue to raise subscription rates across the board and push ads upon customers on their cheapest monthly plans. Disney Plus, Hulu, Max, Netflix, and Paramount Plus all include ads on their most affordable tiers. The monthly cost of Amazon Prime itself isn’t changing, but if you want to preserve the same experience you have today starting on January 29th, you’ll end up paying more.

 

 

Read more:

Amazon Prime Video plans to start showing ads starting on January 29, with an option for customers to pay an additional $2.99 per month to avoid the ads

 

 

— Techmeme

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After testings, South Korean Internet giant Naver plans to let companies use its Rookie office helper robots to deliver meals and parcels

—  Korean tech company ready to export IT systems that direct automated workforce through the 5G cloud

 

 

Song Jung-a / Financial Times:

 

 

At a Starbucks in the futuristic headquarters of Naver, South Korea’s biggest Internet company, a line of robots is on standby to fetch coffee for the company’s employees.

 

About 100 robots on wheels — called Rookies — wander around the offices, carrying out simple tasks such as delivering meals and parcels and testing the boundaries of human interaction with machines in one of the first examples of a robot-friendly building.

PHOTO: Naver’s Rookie robots act as office helpers as they roam from floor to floor in its futuristic headquarters in South Korea © Naver

 

Naver has been experimenting with integrating service robots into office life for more than a year in the 36-storey building on the southern outskirts of Seoul. These “brainless” robots roam around the building, rolling through security gates and taking lifts, powered by Naver’s cloud system that enables them to see, recognize and operate seamlessly.

 

The company is now keen to export the cutting-edge 5G-based cloud robotics technology, with many countries in Europe as well as Japan and Saudi Arabia expressing interest in benchmarking its system.

 

“There are not many companies globally who can offer this high-quality robot service at this scale,” said Seok Sang-ok, chief executive of Naver Labs, Naver’s research and development unit, in an interview with the Financial Times.

 

“This requires a lot of seamless co-operation with many of our affiliates. Naver’s wide-ranging services, including search engines, online shopping and social networking, have allowed us to experiment with various robot technologies and services, all in-house.”

 

Like Amazon, Naver sells products online and operates a sizeable cloud business. It spends about a quarter of its annual sales on R&D with Naver Labs in charge of developing artificial intelligence, robotics and autonomous driving. Naver’s “digital twin” technology — a 3D scan of cities and buildings — also helps the robots to recognise their surroundings and find the most efficient routes. As they operate with just a normal video camera and without advanced processors and navigation tools, it costs much less to make them, Naver says.

 

“We’ve tested the robots for more than a year and now have a lot of data on human interaction with robots,” said Seok.

 

“We’ll focus on exporting IT services, as I believe our robotics technology using the cloud will become much better in two to three years.” Park Sang-soo, a researcher at the Korea Institute for Industrial Economics and Trade, said Naver faced export challenges, with the complexity of its technology meaning it was not as easy as “selling just a fleet of robots.”

 

“Naver’s robots are working well in its offices because the building was designed for that purpose, but it should consider the non-technological factors of the target countries such as their IT infrastructure and regulation to sell its platform solution,” he said.

 

South Korea has a thriving domestic robot industry, most of them being deployed in factories, as the country sees AI and robots as key to alleviating labour shortages in the face of the world’s lowest birth rate.

 

According to the International Federation of Robotics, South Korea has the highest “robot density” in the world, with 1,000 industrial robots per 10,000 manufacturing employees, compared with 399 in Japan, 322 in China, and 274 in the US. Robots are widely used in Korea’s car and semiconductor plants, but they are also becoming an increasingly visible part of day-to-day life.

 

Sales of service robots in South Korea are expected to almost double from $530mn this year to $1bn in 2026, an average annual increase of 23 per cent, according to the Korea Institute of Science and Technology Information. Naver is looking to sell a combination of systems for industrial and server robots. Last month, it opened Asia’s largest data centre to accelerate its push into AI and the cloud. In the vast building in Sejong City that houses 600,000 servers, multiple robots carry heavy servers between IT warehouses and server rooms, while self-driving shuttles are in operation for employees and visitors to the campus.

PHOTO: Naver uses a variety of robots in its vast new data centre, opened in November in Sejong City © Naver

 

“We have a full portfolio [of technologies] that can cover many new use cases,” said Albert Wang, Naver Labs’ principal researcher.

 

“A lot of companies focus on single applications. We are really looking at the system levels. We have multiple types of robot systems co-operating together.”

 

Despite being a technology powerhouse, South Korea remains weak in software development, with its tech exports mostly confined to hardware such as chips, electronics and electric vehicle batteries. Naver is trying to change that picture, with exports of IT services like digital twins, robotics and AI tools, although it has so far failed to gain a foothold abroad with its powerful search engine. Earlier this year, the country won its first major high-tech export contract to the Middle East to build and operate digital twins or virtual versions of five cities including Riyadh, Medina and Mecca, for five years. It is also looking to offer tailored versions of its latest ChatGPT-like artificial intelligence model to foreign governments concerned about US data controls.

 

“We are just beginning to export our IT services, which can become the country’s new export driver,” said Seok. “We aim to become the leading exporter of the country’s IT services in the medium to long term.”

 

 

 

— Techmeme

​

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China struggles to contain a shadow market for business data, as most companies shun the 48 official gov. data exchanges

—  Dozens of marketplaces have sprung up since a 2020 initiative but most transactions still happen on the black market

 

 

Financial Times:

 

China is struggling to reduce the influence of a shadow market for business data, as companies shun the official exchanges that have been set up to tighten control over the sale of information.

 

Local governments across the country have established 48 exchanges, most of them coming after Beijing enshrined data as a national priority in 2020, making it a fifth pillar of production alongside land, labour, capital and entrepreneurship. Under regulatory supervision, government bodies, state-owned enterprises and private companies can buy and sell data on everything from weather patterns to city traffic flows.

 

However, industry insiders and experts say there is no clear incentive for companies to participate in these fledgling marketplaces and that most data sales are still happening off the exchanges.

 

“We are having difficulty attracting participants to enter the marketplace,” said an employee at a state-backed data exchange, adding that the majority of data sales occurred elsewhere.

 

A report published by the Shanghai Data Exchange last month forecast that by 2025, only 10 per cent of data sales would occur on exchanges.

 

The initiative has been part of broader reforms to increase authorities’ control over data after two decades when internet companies such as Tencent and Alibaba created economic fiefdoms powered by vast troves of consumer data. Since 2021, Big Tech has suffered fines for data violations and the Cyberspace Administration of China has been given stronger regulatory powers over how companies procure, manage and store data.

 

Since the 2020 move by the State Council, the country’s cabinet, to make data a factor of production, “the government has put data on a pedestal as something that can be traded”, said Xiang Li, an expert on data management in Hong Kong.

 

Beijing’s stated aim is to unleash productivity by giving more companies access to data that will enable them to deploy artificial intelligence in everything from smart manufacturing to autonomous driving. The value of data bought and sold in China is expected to increase from Rmb88bn ($12.3bn) last year to Rmb516bn ($72.5bn) by the end of the decade as the use of AI grows, according to the Shanghai Data Exchange report.

 

But experts say that the government faces an uphill battle in convincing private companies to sell their data on centralized exchanges rather than through a data broker.

 

The majority of existing data sold on these platforms comes from government bodies, including local transportation and weather bureaus, or from state-owned enterprises (SOEs), which are easier to cajole into handing over their data than private companies, said Kendra Schaefer, head of tech policy at the Beijing-based consultancy Trivium China.

 

According to a Financial Times analysis, the majority of data sold by the 700 merchants on the state-backed Guiyang Global Big Data Exchange, the country’s first such platform, are from state agencies and SOEs.

 

The government of Guizhou province in south-west China, where Guiyang is the capital, has also introduced draft regulations that compel local government bodies and SOEs to hand over their data to the exchange.

 

Companies such as China Southern Power Grid sell customers’ electricity consumption data on Guiyang’s exchange to credit agencies as a new tool to conduct credit checks, according to domestic media reports.

 

The official data exchanges are also designed to provide ways for companies, cash-strapped local governments, and state-owned enterprises to monetise data resources amid slowing economic growth.

 

The official exchanges in Guiyang, Shanghai and Beijing are offering subsidies to incentivise companies to participate.  Even with such incentives, companies are still showing reluctance owing to concerns about getting on the wrong side of data laws restricting the sale of consumer data, according to Trivium’s Schaefer.

 

“We’re at an interesting point in history. Companies are buying and selling this critical economic resource, but the laws surrounding how trading works for this resource don’t exist yet,” she said.

 

The employee at the state-backed exchange, who did not wish to be named, acknowledged that this legal uncertainty prevented it from onboarding new merchants.

“Current data laws are not specific about the legality of data exchanges,” they said.

 

The CAC did not respond to a request for comment.

 

While Beijing had hoped to court data hawkers with the promise of new revenue streams for their data, Schaefer said many companies were also deterred by the high expense of cleaning up their data in preparation for selling on a centralised exchange.

 

“Many companies have poor data management processes, so they need to clean it up before they sell it, which is costly,” she said.

 

“The state wanted companies to jump on board and say: ‘This is an amazing way to make additional revenue from a resource I generate already’,” said Schaefer.

 

“But the reality is that it’s risky and expensive for companies to stick their data on the platforms. The benefit for the companies is unclear.”

 

 

 

— Techmeme

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Hollywood unions against AI to recreate actors’ performances set precedent for future labor movements to prevent automation

—  The year was dominated by talk of what artificial intelligence could do — and what it could do better than most humans.

 

 

Angela Watercutter / Wired:

 

 

Revolt against the machines began at Swingers. And at Bob’s Big Boy, where for weeks Drew Carey picked up the tab. Members of the Writers Guild of America, (WGA), met at both Los Angeles-area diners frequently during their 148-day strike, which hinged on protecting Hollywood’s scribes from being overrun by the march of artificial intelligence.

 

Members of the WGA were just a small part of the resistance. There were others. The Screen Actors Guild—American Federation of Television and Radio Artists, or SAG-AFTRA, soon joined them on the picket lines, together forming a formidable uprising against the perceived threat of AI.

 

What each union was seeking was different. Writers wanted to make sure AI couldn’t be trained on their work or manipulate it without their say-so; actors wanted guardrails on how the technology could be used to recreate their performances. Both parties ended up setting a tone for how labor movements in the future could push back against encroaching automation.

“It is interesting that the Hollywood strikes became the highest-profile example of workers resisting AI in 2023,” says Brian Merchant, author of this year’s Blood in the Machine: The Origins of the Rebellion Against Big Tech, a book about the Luddite movement.

 

At the same time, he adds, the unions’ confrontations with studios came at a time when the boom in AI technology was causing a lot of folks to be critical of Silicon Valley and new tools primed to take their jobs. Originally, the WGA’s AI stipulations didn’t seem like they’d be hotly contested demands—then they became a central issue. “Workers and unions have been fighting automation and certain uses of AI in the workplace for years, of course, but the Writers Guild were among the first to do so after the rise of OpenAI and ChatGPT,” Merchant says. Ultimately, it was the first big face-off between humans and AI, he adds, and “the humans won.”

 

Their timing couldn’t have been better. Throughout 2023, many trades and professions, from painters to coders and beyond, found themselves vulnerable to being replaced by machine learning. IBM’s CEO estimated out loud that some 7,800 jobs at the company could be done by bots in the next five years. A Goldman Sachs report from late March estimated nearly 300,000 jobs globally could be affected by automation. Radiologists, journalists(gulp), tax preparers—everyone, it seemed, spent at least part of 2023 wondering if robots were coming for their jobs.

 

That, in turn, led to increased interest in what protections organized labor could provide workers, even as some unions, like the United Auto Workers and Teamsters, seemed to fall behind on addressing AI’s potential to encroach on jobs. In a recent piece for Harvard Business Review, MIT engineering professor Yossi Sheffi argued short-sightedness on these issues affects both workers and employers, since disengaged staffers could become part of a workforce that’s even less prepared if and when automation comes to their industry.

 

Sheffi wrote the piece in September, when both SAG and WGA were deep into their strikes. At the time, he noted that other industries should “take to heart” what was happening in Hollywood. “Resolving these issues [between the actors and writers and the studios] will take time, but at least in this case, the parties have started the process before AI has become an industry mainstay,” he wrote. “But other unions don’t seem to be facing up to the ways technological advances will change jobs.”

AS THE ADVANCE of AI marched on throughout 2023, it became clear that unions were only part of the resistance. Authors, worried that large language models had been trained using their books, filed a handful of lawsuits against OpenAI, Meta, Microsoft, and others. So did visual artists, against Stable Diffusion,

 

Midjourney, DeviantArt, and more. None of those suits has reached any kind of conclusion, and some argue copyright claims aren’t the way to stop the bots from absorbing creative work, but the suits did turn the courts into yet another battlefield, in addition to picket lines, on which humans pushed back against AI incursion.

 

By the end of 2023, governments entered the fray. In early November, US president Joe Biden signed an executive orderattempting, among other things, to curtail AI’s impact on human work and provide “federal support for workers facing labor disruptions, including from AI.” Unions, including SAG, praised the move, which came as world leaders were heading to the UK for the AI Safety Summit, where, as my colleague Will Knight wrote, they sought to contain the threats of machine learning while also harnessing its power.

 

That has always been the tricky part. From weavers to writers, lots of people use machines to improve their work. Automation helps! As AI boosters will tell you, the technology can cultivate new forms of creativity. People can write books alongside AI, create new styles of visual art, build infinite Seinfeld generators. Some Hollywood writers use the tools for basic brainstorming tasks. Fear comes in when brainstorming evolves into a studio head asking ChatGPT to write a new movie about a cat and a cop who are best friends. No scribes needed.

 

Currently, chatbots can’t whip up fully formed scripts, or novels, or Caravaggios, but the tech is evolving so quickly it feels all but imminent. When Sam Altman was briefly ousted from OpenAI in November, there was all kinds of speculation that the company was developing its tech too quickly, that its for-profit ambitions had overwhelmed its altruistic intentions. Altman is now back at the head of his company, but whether or not OpenAI is still evolving too quickly remains to be seen. But Microsoft does now have a nonvoting board seat.

 

Funny thing about that: Microsoft actually offered jobs to OpenAI staffers during that brief period when Altman was voted off the island. So did Salesforce. OpenAI employees all but told Salesforce CEO Marc Benioff to go screw, but the sentiment stood as a reminder that while AI is poised to take many jobs, it also creates jobs in AI. The “learn to code” crowd has all new ammo. Even Biden’s executive order was clear about the fact that the US government wanted to attract the best and brightest in the field.

 

But that’s job creation, not job displacement. New technologies create jobs all the time, but with AI, some of those jobs pay pennies. What’s more, AI can also ask you to train it to do your job before picking up your tools. Going forward, the likelihood that AI will displace many entry-level jobs while creating a few highly skilled gigs seems high. The biggest questions in AI right now nearly all revolve around what these machines are learning from people, whether it’s human skill or human bias.

 

 

 

— Techmeme

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Amazon faces challenges in selling cars in the US: Only 11% of its customers report buying $1k+ items, dealerships sell most new cars

—  Company aims to make online car purchases as seamless as getting everyday essentials

 

Sebastian Herrera / Wall Street Journal:

 

—  Willie Hall loves to browse and buy cars online, but he wants more options. Soon, he may turn to Amazon.com.

 

“I’m already a Prime member,” said Hall, who lives in Colorado and bought a used Fiat 500 Abarth on Carvana in 2021. “I’ve been with Amazon for God knows how long and know the way they operate.”

 

Amazon AMZN -0.01%decrease; red down pointing triangle is eager to see just how many Willie Halls there are in the U.S. The company last month said shoppers next year will be able to browse, finance and complete a purchase of Hyundai vehicles on Amazon. Shoppers will only have to visit a dealership to pick up their car; the company is also working on delivering the vehicles.

 

Car sales represent Amazon’s next bet in e-commerce dominance and come after the Covid-19 pandemic made online car purchases more popular. Amazon executives want to make buying vehicles through its website as simple as purchasing toilet paper or dog food, and the company is looking to strike broad partnerships with carmakers.

The company is set to face several challenges in expanding the program beyond a pilot phase for employees starting early next year: One is dealerships, which remain at the center of most new-car sales and depend on service revenue for profit incentives. A second will be trying to get customers who visit its website mainly for lower-priced items to turn to the platform for one of the biggest purchases of their lives. Amazon also will have to navigate different government regulations.

 

“Customers tell us it’s really hard to buy a car,” Fan Jin, Amazon’s director of vehicle sales, said in an interview. Vehicle-buying software is fragmented, with dealers using a range of software providers. Varying regulations across states also make it difficult. “It’s a process that we’ve heard time and again could use improvement, and we have an opportunity to go and prove it,” she said.

When the new service launches later next year, Amazon said shoppers will be able to complete every step of the car-buying process through its website. Only new Hyundai vehicles will be available at the start. Consumers will have different financing options, but the company said it is still working through details. Eventually, Amazon wants to expand to trade-in vehicles and used cars.

Many dealers might be loath to accept a high volume of online sales because they make a significant amount of money on service and warranty deals that customers agree to when they finance a car purchase.

 Caption – Amazon and Hyundai executives spoke during a press conference in Los Angeles last month. PHOTO credits: ROBYN BECK/AGENCE FRANCE-PRESSE/GETTY IMAGES

Mike Sullivan, who runs a Hyundai dealership in Santa Monica, Calif., that is part of the pilot program, views the Amazon partnership as a positive step. Salespeople at the dealership could make half as much per sale in commission in online sales versus in person, he said, but the upside is the time spent on those sales is expected to be far less. Overall compensation could increase, he said.

During the height of the pandemic, Sullivan and many auto-sales professionals learned to embrace online sales. His dealerships sold about 300 cars online during the health crisis. Selling with Amazon could be easier, because “we now have the power of Amazon guiding these people to us,” he said.

Another issue is that Amazon will be trying to get customers to think of its platform for car-buying. The typical transaction on Amazon is under $50, according to a recent survey by Consumer Intelligence Research Partners, which studies Amazon customer habits. Only 11% of customers surveyed reported spending $1,000 or more on a single item.

“They’re great at getting you to spend $30 or $40, but it’s hard to break through to the bigger stuff,” said Josh Lowitz, co-founder of the research firm. “The bigger stuff is more infrequent, and so it’s more special for the customer.”

Jin, Amazon’s director of vehicle sales, said while many people go to Amazon for everyday purchases, the company also has an established base that makes infrequent, higher-priced purchases for items such as furniture and electronics.

Some analysts estimate that two-thirds of customers already know what they want before purchasing their vehicles, with many people conducting their research on the web. But even if Amazon customers are ready for online car purchases, signing new carmakers will be complex and will depend on how much the Hyundai partnership succeeds, said Chris Sutton, vice president of automotive retail at consumer-data analytics firm J.D. Power.

Amazon and Hyundai first partnered in 2021 through an online Hyundai showroom where viewers could “build” a car and locate inventory. Amazon said consumers responded positively to the showroom, and the company surveyed shoppers who indicated they were interested in going through the entire car-buying process with Amazon.

To entice Hyundai, Amazon struck a broad business partnership that included cloud computing, advertising and integration of its Alexa technology in the brand’s cars beginning in 2025. It is also expected to provide dealers with performance data. AWS customers who make long-term cloud commitments can pay lower rates.

The company has turned to more corporate partnerships in numerous other business segments in recent months, including a partnership with Meta Platforms’ Instagram for product sales and a logistics deal with Canadian e-commerce company Shopify.

 

 

— Techmeme

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Cenntro regains compliance with Nasdaq minimum bid price rule

FREEHOLD, N.J. — (BUSINESS WIRE) — Cenntro Electric Group Limited (NASDAQ: CENN) (“mCenntro” or “the Company”), a leading electric vehicle technology company with advanced, market-validated electric commercial vehicles, announced today that on Dec. 22, 2023, the Company received written notice from The Nasdaq Stock Market LLC (“Nasdaq”) that for the ten consecutive business days from Dec. 8, 2023, to Dec. 21, 2023, the closing bid price of the Company’s common stock has been at $1.00 per share or greater. Accordingly, Cenntro has regained compliance with Nasdaq Listing Rule 5550(a)(2).

About Cenntro Electric Group Ltd.

Cenntro Electric Group Ltd. (or “Cenntro”) (NASDAQ: CENN) is a leading designer and manufacturer of electric commercial vehicles. Cenntro’s purpose-built ECVs are designed to serve a variety of organizations in support of city services, last-mile delivery, and other commercial applications. Cenntro plans to lead the transformation in the automotive industry through scalable, decentralized production, and smart driving solutions empowered by the Cenntro iChassis. For more information, please visit Cenntro’s website at: www.cenntroauto.com.

 

Forward-Looking Statements

This communication contains “forward-looking statements” within the meaning of the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Forward-looking statements include all statements that are not historical facts. Such statements may be, but need not be, identified by words such as “may,” “believe,” “anticipate,” “could,” “should,” “intend,” “plan,” “will,” “aim(s),” “can,” “would,” “expect(s),” “estimate(s),””project(s),” “forecast(s)”, “positioned,” “approximately,” “potential,” “goal,” “strategy,” “outlook” and similar expressions. Examples of forward-looking statements include, among other things, statements regarding assembly and distribution capabilities, decentralized production, and fully digitalized autonomous driving solutions. All such forward-looking statements are based on management’s current beliefs, expectations and assumptions, and are subject to risks, uncertainties and other factors that could cause actual results to differ materially from the results expressed or implied in this communication. For additional risks and uncertainties that could impact Cenntro’s forward-looking statements, please see disclosures contained in Cenntro’s public filings with the SEC, including the “Risk Factors” in Cenntro’s Annual Report on Form 10K/A filed with the Securities and Exchange Commission on July 6, 2023 and which may be viewed at www.sec.gov.

Contacts

Investor Relations Contact:
Chris Tyson

MZ North America

CENN@mzgroup.us
949-491-8235

Company Contact:
PR@cenntroauto.com
IR@cenntroauto.com

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CCM Biosciences announces launch of 5Prime Sciences business unit

New business unit is focused on DNA Biotechnology and Molecular Diagnostics, leveraging state-of-the-art platforms for enzyme engineering

 

Global annual revenue from company’s intellectual property portfolio is $30-50M

 

 

MOUNT LAUREL, N.J. — (BUSINESS WIRE) — Diversified biotechnology company CCM Biosciences (CCM Bio) announced the launch of its business unit CCM 5Prime Sciences (5Prime) focused on the development and application of proprietary technology in the domain of DNA biotechnology. 5Prime’s technology platform includes multiple patent-protected, globally commercialized compositions and methods for molecular cloning, next-generation DNA sequencing and molecular diagnostics.

 

5Prime has two focus areas: 1) in vitro diagnostic (IVD) tests: a wide array of companion diagnostics (CDx) tests for targeted cancer, rare disease, and prenatal/preimplantation diagnostics, developed using the droplet digital Polymerase Chain Reaction (ddPCR) and Next-Generation Sequencing (NGS) methodologies, which accompany the personalized medicine therapeutic (Rx) pipeline of CCM Bio; 2) synthetic biology: engineered DNA- and RNA-manipulating enzymes that improve upon the enzymes used in IVD tests, in PCR reagents, and also in enzymatic DNA/RNA synthesis.

 

Proven technology behind market-leading DNA sequencing products and diagnostic tests; including one of the 5 highest revenue-generating technologies invented in the history of Princeton University

 

Focus areas 1 and 2 are based on the company’s patented technology originating in the PhD thesis work of Co-Founder and CEO Dr. Raj Chakrabarti at Princeton University. According to the Princeton University Office of Technology Licensing, patents in this portfolio, which are now controlled by 5Prime, are among the top 5 revenue-generating patents in the history of the university, having been commercialized in collaboration with companies such as Celera Diagnostics, Quest Diagnostics, Abbott, New England Biolabs, and Toyobo Life Sciences. Diagnostic tests and products based on the company’s intellectual property include the XSense test from Quest Diagnostics, which is the leading DNA-based carrier screening test for autism (Fragile X syndrome); and the Q5 polymerase kit marketed by New England Biolabs, which is the leading high-fidelity polymerase kit for DNA sequencing.

 

In the context of molecular diagnostics, NGS is typically applied to diagnose in high-throughput the patterns of DNA mutations in genes. A related method called RNA-Seq, which applies NGS to RNA rather than DNA to measure real-time gene expression levels, has emerged as a foundation for modern personalized medicine. However, a notorious difficulty in both traditional NGS and RNA-Seq is sequence bias, which results in inaccurate estimates of the relative copy numbers of different genes and associated disease-causing mutations, and which has limited the transformative potential of these methods. ddPCR is a sensitive method for diagnosing mutations in specific disease-associated genes that is also limited by problems of sequence bias.

 

5Prime’s technology enables the efficient polymerization and amplification of nearly any DNA or RNA sequence to overcome sequence bias in nucleic acid amplification and associated diagnostic methods like NGS and ddPCR, the global markets for which were valued at $10B and $6B, respectively, in 2022 and expected to surpass $44B and $14B, respectively, by 2032. Its state-of-the-art synthetic biology platform for polymerase enzyme engineering generates proprietary polymerases with optimal properties for NGS or PCR-based diagnostic tests, by applying machine learning algorithms to the big data generated from ultrahigh-throughput, microfluidic experimental screening of enzyme activity. In addition, the company’s technology platform applies proprietary nonaqueous media and computational systems biology methods in conjunction with such enzymes to dramatically improve nucleic acid polymerization and amplification efficiency.

 

About CCM Biosciences

CCM Biosciences, Inc. is a biotechnology company dedicated to discovering and developing novel drugs – including small molecules, gene therapies, biologics, and nanomedicines – as well as associated companion diagnostics. CCM Bio’s patented molecular discovery platforms were developed at Chakrabarti Advanced Technology, a privately funded R&D institute founded in 2010 with scientists in the US, France and India and with publications in leading scientific journals including PNAS, Nucleic Acids Research, American Chemical Society journals and Nature Publishing Group journals. CCM Bio is partnered with the global chemical and pharmaceutical services company PMC Group, Inc. for fully integrated discovery, development and manufacturing of drugs and diagnostics.

Contacts

Dr. Anisha Ghosh
email: anisha@ccm-bio.com

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A study estimates that there are 13.3B+ videos on YouTube, with 4B+ posted to its platform in 2023; median YouTube video has 39 views

—  I got interested in this question a few years ago, when I started writing about the “denominator problem.”

 

Ethan Zuckerman:

 

 

— A great deal of social media research focuses on finding unwanted behavior – mis/disinformation, hate speech – on platforms. This isn’t that hard to do: search for “white genocide” or “ivermectin” and count the results. Indeed, a lot of eye-catching research does just this – consider Avaaz’s August 2020 report about COVID misinformation. It reports 3.8 billion views of COVID misinfo in a year, which is a very big number. But it’s a numerator without a denominator – Facebook generates dozens or hundreds of views a day for each of its 3 billion users – 3.8 billion views is actually a very small number, contextualized with a denominator.

 

A few social media platforms have made it possible to calculate denominators. Reddit, for many years, permitted Pushshift to collect all Reddit posts, which means we can calculate what a small fraction of Reddit is focused on meme stocks or crypto, versus conversations about mental health or board gaming. Our Redditmap.social platform – primarily built by Virginia Partridge and Jasmine Mangat – is based around the idea of looking at the platform as a whole and understanding how big or small each community is compared to the whole. Alas, Reddit cut off public access to Pushshift this summer, so Redditmap.social can only use data generated early this year.

 

Twitter was also a good platform for studying denominators, because it created a research API that took a statistical sample of all tweets and gave researchers access to every 10th or 100th one. If you found 2500 tweets about ivermectin a day, and saw 100m tweets through the decahose (which gave researchers 1/10th of tweet volume), you could calculate an accurate denominator (100m x 10) (All these numbers are completely made up.) Twitter has cut off access to these excellent academic APIs and now charges massive amounts of money for much less access, which means that it’s no longer possible for most researchers to do denominator-based work.

 

Interesting as Reddit and Twitter are, they are much less widely used than YouTube, which is used by virtually all internet users. Pew reports that 93% of teens use YouTube – the closest service in terms of usage is Tiktok with 63% and Snapchat with 60%. While YouTube has a good, well-documented API, there’s no good way to get a random, representative sample of YouTube. Instead, most research on YouTube either studies a collection of videos (all videos on the channels of a selected set of users) or videos discovered via recommendation (start with Never Going to Give You Up, objectively the center of the internet, and collect recommended videos.) You can do excellent research with either method, but you won’t get a sample of all YouTube videos and you won’t be able to calculate the size of YouTube.

 

I brought this problem to Jason Baumgartner, creator of PushShift, and prince of the dark arts of data collection. One of Jason’s skills is a deep knowledge of undocumented APIs, ways of collecting data outside of official means. Most platforms have one or more undocumented APIs, widely used by programmers for that platform to build internal tools. In the case of YouTube, that API is called “Inner Tube” and its existence is an open secret in programmer communities. Using InnerTube, Jason suggested we do something that’s both really smart and really stupid: guess at random URLs and see if there are videos there.

 

Here’s how this works: YouTube URLs look like this: https://www.youtube.com/ watch?v=vXPJVwwEmiM

 

That bit after “watch?v=” is an 11 digit string. The first ten digits can be a-z,A-Z,0-9 and _-. The last digit is special, and can only be one of 16 values. Turns out there are 2^64 possible YouTube addresses, an enormous number: 18.4 quintillion. There are lots of YouTube videos, but not that many. Let’s guess for a moment that there are 1 billion YouTube videos – if you picked URLs at random, you’d only get a valid address roughly once every 18.4 billion tries.

 

We refer to this method as “drunk dialing”, as it’s basically as sophisticated as taking swigs from a bottle of bourbon and mashing digits on a telephone, hoping to find a human being to speak to. Jason found a couple of cheats that makes the method roughly 32,000 times as efficient, meaning our “phone call” connects lots more often. Kevin Zheng wrote a whole bunch of scripts to do the dialing, and over the course of several months, we collected more than 10,000 truly random YouTube videos.

 

There’s lots you can do once you’ve got those videos. Ryan McGrady is lead author on our paper in the Journal of Quantitative Description, and he led the process of watching a thousand of these videos and hand-coding them, a massive and fascinating task. Kevin wired together his retrieval scripts with a variety of language detection systems, and we now have a defensible – if far from perfect – estimate of what languages are represented on YouTube. We’re starting some experiments to understand how the videos YouTube recommends differ from the “average” YouTube video – YouTube likes recommending videos with at least ten thousand views, while the median YouTube video has 39 views.

 

I’ll write at some length in the future about what we can learn from a true random sample of YouTube videos. I’ve been doing a lot of thinking about the idea of “the quotidian web”, learning from the bottom half of the long tail of user-generated media so we can understand what most creators are doing with these tools, not just from the most successful influencers. But I’m going to limit myself to the question that started this blog post: how big is YouTube?

 

Consider drunk dialing again. Let’s assume you only dial numbers in the 413 area code: 413-000-0000 through 413-999-9999. That’s 10,000,000 possible numbers. If one in 100 phone calls connect, you can estimate that 100,000 people have numbers in the 413 area code. In our case, our drunk dials tried roughly 32k numbers at the same time, and we got a “hit” every 50,000 times or so. Our current estimate for the size of YouTube is 13.325 billion videos – we are now updating this number every few weeks at tubestats.org.

 

Once you’re collecting these random videos, other statistics are easy to calculate. We can look at how old our random videos are and calculate how fast YouTube is growing: we estimate that over 4 billion videos were posted to YouTube just in 2023. We can calculate the mean and median views per video, and show just how long the “long tail” is – videos with 10,000 or more views are roughly 4% of our data set, though they represent the lion’s share of views of the YouTube platform.

 

Perhaps the most important thing we did with our set of random videos is to demonstrate a vastly better way of studying YouTube than drunk dialing. We know our method is random because it iterates through the entire possible address space. By comparing our results to other ways of generating lists of YouTube videos, we can declare them “plausibly random” if they generate similar results. Fortunately, one method does – it was discovered by Jia Zhou et. al. in 2011, and it’s far more efficient than our naïve method. (You generate a five character string where one character is a dash – YouTube will autocomplete those URLs and spit out a matching video if one exists.) Kevin now polls YouTube using the “dash method” and uses the results to maintain our dashboard at Tubestats.

 

We have lots more research coming out from this data set, both about what we’re discovering and about some complex ethical questions about how to handle this data. (Most of the videos we’re discovering were only seen by a few dozen people. If we publish those URLs, we run the risk of exposing to public scrutiny videos that are “public” but whose authors could reasonably expect obscurity. Thus our paper does not include the list of videos discovered.) Ryan has a great introduction to main takeaways from our hand-coding. He and I are both working on longer writing about the weird world of random videos – what can we learn from spending time deep in the long tail?

 

Perhaps most importantly, we plan to maintain Tubestats so long as we can. It’s possible that YouTube will object to the existence of this resource or the methods we used to create it. Counterpoint: I believe that high level data like this should be published regularly for all large user-generated media platforms. These platforms are some of the most important parts of our digital public sphere, and we need far more information about what’s on them, who creates this content and who it reaches.

 

Many thanks to the Journal for Quantitative Description of publishing such a large and unwieldy paper – it’s 85 pages! Thanks and congratulations to all authors: Ryan McGrady, Kevin Zheng, Rebecca Curran, Jason Baumgartner and myself. And thank you to everyone who’s funded our work: the Knight Foundation has been supporting a wide range of our work on studying extreme speech on social media, and other work in our lab is supported by the Ford Foundation and the MacArthur Foundation.

 

Finally – I’ve got COVID, so if this post is less coherent than normal, that’s to be expected. Feel free to use the comments to tell me what didn’t make sense and I will try to clear it up when my brain is less foggy.

 

 

 

— Techmeme

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Data.ai: Puzzle app Royal Match globally held top spot for biggest mobile game by monthly revenue since July, beating Candy Crush Saga

—  Istanbul-based developer Dream Games is on track to double revenue from its debut title despite a lacklustre year for mobile peers

 

 

Tim Bradshaw / Financial Times:

 

Puzzle app Royal Match, developed by a small team in Istanbul, has overtaken Microsoft-owned Candy Crush Saga as the most lucrative mobile game in the world, outshining other smartphone titles during a lacklustre 12 months for the industry. Royal Match became the biggest mobile game by monthly revenue globally in July and has held the top spot since then, according to Data.ai, which tracks consumer spending on Apple and Android app stores.

 

Launched in 2021, it is the debut title from Dream Games, a Turkish start-up valued at $2.75bn early last year. For more than a decade, King’s Candy Crush Saga has been one of the world’s most consistently popular games on any platform, hitting $20bn in cumulative revenue this year. Now part of Microsoft after its $75bn buyout of Activision Blizzard, Candy Crush has spent only six months outside the top 10 highest-revenue mobile games since it was released in late 2012, according to Data.ai. Consumer spending on Royal Match more than doubled in the year to October, increasing the game’s annual gross revenue run rate (before paying out app store fees) to $2bn, said Soner Aydemir, Dream Games co-founder and chief executive.

 

Royal Match grew so much in what has been another challenging year for mobile games, its creators and investors say, thanks to a focus on quality and mass-market appeal, in a sector that often sees short-term money-spinners launched into Apple’s and Google’s app stores by a few developers on a low budget. “We strongly believe quality is the best business plan,” Aydemir said. Data.ai is forecasting the mobile games market will decline about 3 per cent this year globally, including in China, making Royal Match — alongside Scopely’s Monopoly Go! — a scarce new hit. “They have had a very impressive year,” said Lexi Sydow, head of insights at Data.ai. Royal Match is a “match-three” puzzle game, which would typically involve lining up tiles or icons to clear a grid. These have become the most popular casual gaming genre since they were popularised by Bejeweled in the early 2000s.

PHOTO: Soner Aydemir, Dream Games co-founder and chief executive: ‘What we are focusing on is a little bit different to our competitors’ © Ege Islek

 

While it spawned many imitators, Candy Crush Saga came to dominate the match-three market, ranking number one by consumer spend on mobile app stores for nearly 127 consecutive months, according to Data.ai. At least, until this summer. Aydemir said his players are more loyal and willing to spend more on in-game items than in other puzzle apps. More than 90 per cent of Royal Match users who have played the game for a year go on to play it for a second year, he added. Part of Royal Match’s success is its mass-market appeal, with an easy-to-learn puzzle element and bright and breezy storyline that draws a wider audience than the fantasy battlers or casino games that typically dominate the revenue charts, Sydow said. With about 55mn monthly active users, it has succeeded in persuading players to spend more on average than Candy Crush’s much larger audience of approximately 160mn does, according to Data.ai. Dream Games’ investors are hoping that it can outlast other pretenders to Candy Crush’s throne, such as Playrix’s Gardenscapes and Homescapes, which briefly outsold King’s hit for a few months in 2020.

 

“So many mobile games are a bit glitchy or the graphics aren’t that good but Royal Match is a luxury experience,” said Rob Moffat, an early investor in Dream Games with Balderton Capital, the London-based venture capital firm. “Nothing ever breaks, it’s a really clear clean art style. They think about every detail.” Dream has also invested heavily in advertising to bring in new players and lure back lapsed ones, at a time when many mobile games developers have struggled to navigate Apple’s privacy changes, which have impeded ad targeting of “whales” or big spenders in the past few years. “There’s this idea that in a climate where it’s more difficult to find your whales, it might be smarter to go broader,” said Sydow.

PHOTO: ‘Royal Kingdom’, the coming follow-up to ‘Royal Match’ © Dream Games

 

Next year, Dream Games plans to capitalise on its success by launching a follow-up, Royal Kingdom, that Aydemir hopes will “extend the story and the universe” of Match’s lead character, King Robert. Royal Kingdom, which introduces Robert’s brother Richard, is being tested in the UK and other select markets. “What we are focusing on is a little bit different to our competitors,” said Aydemir. “We are focusing on building an [intellectual property] and characters and a universe, with a well-crafted product to create a high-quality game with long-term and mass appeal.” Dream Games wants to avoid being a “one-hit wonder”, said Danny Rimer, a partner at investor Index Ventures, who sits on its board. “They have higher expectations for themselves.” The start-up was founded in 2019 by former executives at Peak Games, another Turkish mobile developer that was acquired in 2020 by US rival Zynga. Dream Games, which now employs 200 people and is profitable, recently brought on Ed Catmull, co-founder of digital animation pioneer Pixar, as a strategic adviser.

 

“When I first started playing Royal Match, I was struck by the unusual attention to the quality of the game’s visuals,” said Catmull, who has passed 5,000 levels on the game, according to Aydemir. Aydemir is an admirer of Pixar and its parent, Walt Disney, for both their output and their organising principles, and has watched The Lion King musical five times and the Frozen stage show twice. Dream Games has a 35-seat cinema in its Istanbul office where all staff, including software engineers, regularly watch movies — then spend hours afterwards analysing what makes them good or bad. “It builds a creative culture in the company,” Aydemir said. “We also play very bad games to understand why they are not good enough.”

 

 

 

— Techmeme