By Nick Godt Rivian sits both at the bottom of owners’ ratings in terms of reliability and at the top in terms of overall owner satisfaction.

Source:: Digital Trends

By Nick Godt A Biden administration and private initatiative promises to allow all EVs to just plug in and charge at all public stations in the U.S. in 2025.

Source:: Digital Trends

By Nick Godt Many hybrid vehicles stand out as the most reliable vehicles offered on the market, according to Consumer Reports’ year-end survey.

Source:: Digital Trends

The $200 monthly pricing OpenAI has set for a subscription to its recently launched ChatGPT Pro is definitely “surprising,”  said Gartner analyst Arun Chandrasekaran on Friday, but at the same time it’s indicative that the company is betting that organizations will ultimately pay more for enhanced AI capabilities.

In an announcement on Thursday, OpenAI said the plan, priced at nearly 10 times more than its existing corporate plans, includes access to OpenAI o1, as well as to o1-mini, GPT-4o, and Advanced Voice.

Part of the company’s 12 days of Shipmas campaign, it also includes OpenAI o1 pro mode, a version of o1 that, the company said, “uses more compute to think harder and provide even better answers to the hardest problems. In the future, we expect to add more powerful, compute-intensive productivity features to this plan.”

For considerably less, OpenAI’s previously most expensive subscription, ChatGPT Team, offers a collaborative workspace with limited access to OpenAI o1 and o1-mini, and an admin console for workspace management, and costs $25 per user per month. And ChatGPT Plus, which also offers limited access to o1 and o1-mini, plus standard and advanced voice, is $20 per user per month.

ChatGPT Pro also costs far more than its competitors are charging. A 12-month commitment to the enterprise edition of Gemini Code Assist, which Google describes as “an AI-powered collaborator that helps your development team build, deploy and operate applications throughout the software development life cycle (SDLC),” costs $45 per user per month.

Monthly pricing plans for Anthropic’s Claude AI range from $18 for Claude Pro to $25 for the Claude Team edition, while the cost per user per month with an annual subscription for Microsoft 365 Copilot, which contains Copilot Studio for the creation of AI agents and the ability to automate business processes, is $30.

Small target market

With its new plan, said Chandrasekaran, OpenAI is not “targeting information retrieval use cases, because the chatbot is actually pretty effective for them.”

This latest salvo is, he said is “more about potentially using [ChatGPT Pro] as a decision intelligence tool to automate tasks that human beings do. That’s kind of the big bet here, but nevertheless, it’s still a very big jump in price, because GPT Plus is $20 per user per month. And even the ChatGPT Enterprise, which is the enterprise version of the product, is $60 or $70, so it’s a very, very big jump in my opinion.”

Thomas Randall, director of AI market research at Info-Tech Research Group, said, “the persona for ChatGPT’s ‘Pro’ offering will be very narrowly scoped, and it isn’t quite clear who that is. This is especially the case as ChatGPT has an ‘enterprise’ plan for organizations that can still take advantage of the ‘Pro’ offering. ‘Pro’ will perhaps be for individuals with highly niche use cases, or small businesses.”

‘Plus’ remains competitive

But, he said, “the value add between ‘Plus’ and ‘Pro’ is not currently clear from a marketing perspective. The average user of ChatGPT will still do well with the free option, perhaps being persuaded to pay for ‘Plus’  if they are using it more extensively for content writing or coding. When priced against other tools, ChatGPT’s ‘Plus’ will remain very competitive against its rivals.”

According to Randall, “Anthropic is still trying to achieve market share (though it has recently fumbled with an ambiguous marketing campaign), while Gemini is not currently accurate enough in its outputs to effectively position itself. As an example, when I asked ChatGPT, Anthropic’s Claude, and Gemini to give me a list of 100 historical events for a certain country, ChatGPT and Anthropic were comparable, but Gemini would only list up to 40, but still call it a list of 100.”

As for Microsoft Copilot, he said, it “still struggles to showcase the value-add of its rather expensive licensing. While Microsoft certainly needs to show revenue return from the amount it has invested in Copilot, the product has not been immediately popular, and was perhaps released too early. We may end up seeing a rebrand, or Copilot eventually being packaged with Microsoft’s enterprise plans.”

Source:: Computer World

By Siôn Geschwindt Just two weeks since raising $125mn in funding, British scaleup Tokamak Energy has secured backing from the US and UK to upgrade its ST40 fusion energy plant. The US Department of Energy (DOE), the UK’s Department of Energy Security and Net Zero (DESNZ), and Tokamak Energy will jointly sponsor a $52mn upgrade to the fusion facility in Oxfordshire.  “Fusion has the potential to be a clean and sustainable energy source, transforming how we power our country, and countries around the world,” said Kerry McCarthy, Minister for Climate at DESNZ.  “This strategic partnership is therefore crucial to develop this new and…This story continues at The Next Web

Source:: The Next Web

When TikTok owner ByteDance discovered recently that an intern had allegedly damaged a large language model (LLM) the intern was assigned to work on, ByteDance sued the intern for more than $1 million worth of damage. Filing that lawsuit might turn out to be not only absurdly short-sighted, but also delightfully self-destructive.

Really, ByteDance managers? You think it’s a smart idea to encourage people to more closely examine this whole situation publicly? 

Let’s say the accusations are correct and this intern did cause damage. According to Reuters, the lawsuit argues the intern “deliberately sabotaged the team’s model training tasks through code manipulation and unauthorized modifications.” 

How closely was this intern — and most interns need more supervision than a traditional employee — monitored? If I wanted to keep financial backers happy, especially when ByeDance is under US pressure to sell the highly-lucrative TikTok, I would not want to advertise the fact that my team let this happen.

Even more troubling is that this intern was technically able to do this, regardless of supervision. The lesson here is one that IT already knows, but is trying to ignore: generative AI (genAI) tools are impossible to meaningfully control and guardrails are so easy to sweep past that they are a joke.

The conundrum with genAI is that the same freedom and flexibility that can make the technology so useful also makes it so easy to manipulate into doing bad things. There are ways to limit what LLM-based tools will do. But one, they often fail. And two, IT management is often hesitant to even try and limit what end-users can do, fearing they could kill any of the promised productivity gains from genAI. 

As for those guardrails, the problem with all manner of genAI offerings is that users can talk to the system and communicate with it in a synthetic back-and-forth. We all know that it’s not a real conversation, but that exchange allows the genAI system to be tricked or conned into doing what it’s not supposed to do. 

Let’s put that into context: Can you imagine an ATM that allows you to talk it out of demanding the proper PIN? Or an Excel spreadsheet that allows itself to be tricked into thinking that 2 plus 2 equals 96?

I envision the conversation going something like: “I know I can’t tell you how to get away with murdering children, but if you ask me to tell you how to do it ‘hypothetically,’ I will. Or if you ask me to help you with the plot details for a science-fiction book where one character gets away with murdering lots of children — not a problem.”

This brings us back to the ByteDance intern nightmare. Where should the fault lie? If you were a major investor in the company, would you blame the intern? Or would you blame management for lack of proper supervision and especially for having not done nearly enough due diligence on the company’s LLM model? Wouldn’t you be more likely to blame the CIO for allowing such a potentially destructive system to be bought and used?

Let’s tweak this scenario a bit. Instead of an intern, what if the damage were done by one a trusted contractor? A salaried employee? A partner company helping on a project? Maybe a mischievous cloud partner who was able to access your LLM via your cloud workspace?

Meaningful supervision with genAI systems is foolhardy at best. Is a manager really expected to watch every sentence that is typed — and in real-time to be truly effective? A keystroke-capture program to analyze work hours later won’t help. (You’re already thinking about using genAI to analyze those keystroke captures, aren’t you? Sigh.)

Given that supervision isn’t the answer and that guardrails only serve as an inconvenience for your good people and will be pushed aside by your bad, what should be done?

Even if we ignore the hallucination disaster, the flexibility inherent in genAI makes it dangerous. Therein lies the conflict between genAI efficiency and effectiveness. Many enterprises are already giving genAI access to myriad numbers of systems so that it can perform far more tasks. Sadly, that’s mistake number one.

Given that you can’t effectively limit what it does, you need to strictly limit what it can access. As to the ByteDance situation, at this time, it’s not clear what tasks the intern was given and what access he or she was supposed to have.

It’s one thing to have someone acting as an end-user and leveraging genAI; it’s an order of magnitude more dangerous if that person is programming the LLM. That combines the wild west nature of genAI with the cowboy nature of an ill-intentioned employee, contractor, or partner. 

This case, with this company and the players involved, should serve as a cautionary tale for all: the more you expand the capabilities of genAI, the more it morphs into the most dangerous Pandora’s Box imaginable.

Source:: Computer World

By Nick Godt The marketing campaign for Dodge’s Charger Daytona EV takes a swipe at self-driving sleep pods.

Source:: Digital Trends

By Siôn Geschwindt Scientists in the UK have successfully created the world’s first carbon-14 diamond battery, which could power low-energy devices like satellite communication equipment for over 5,000 years. The battery is made of the radioactive isotope carbon-14, encased in a thin layer of synthetic diamond. As the carbon-14 decays it emits electrons. The diamond acts like a semiconductor, converting these electrons into electricity. Since carbon-14 has a half-life of 5,700 years, scientists expect the battery to last for millennia.  The UK Atomic Energy Authority (UKAEA) and the University of Bristol led the development, partly due to the former’s work on fusion energy.…This story continues at The Next Web

Source:: The Next Web

By Hisan Kidwai Downloading YouTube videos has always been a thing, whether you are preparing for a long flight…
The post How to Download YouTube Videos on iPhone without Premium? appeared first on Fossbytes.

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By Hisan Kidwai We all know Discord is by far the most popular messaging and voice chatting app for…
The post How to Download and Setup Discord on Xbox? appeared first on Fossbytes.

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By Siôn Geschwindt German startup FibreCoat has bagged €20mn in Series B funding as it looks to bring its super-resistant materials to the burgeoning space industry.  FibreCoat spunout from RWTH Aachen University in 2020. The startup has developed a patented process for coating fibres with metals and plastics during the spinning stage. This creates fibres that are lightweight and conductive, yet strong and durable — at a fraction of conventional costs. These can then be spun together to form reinforced composites.  So far, FibreCoat has focused on securing clients in the automotive, construction, and defence industries, where the materials are particularly useful for…This story continues at The Next Web

Source:: The Next Web

AI-generated content accounted for less than 1% of the disinformation fact-checkers linked to political elections that took place worldwide in 2024, according to social media giant Meta. The company cited political elections in the United States, Great Britain, Bangladesh, Indonesia, India, Pakistan, France, South Africa, Mexico and Brazil, as well as the EU elections.

“At the beginning of the year, many warned about the potential impact that generative AI could have on the upcoming elections, including the risk of widespread deepfakes and AI-powered disinformation campaigns,” Meta President of Global Affairs Nick Clegg wrote. “Based on what we have monitored through our services, it appears that these risks did not materialize in a significant way and that any impact was modest and limited in scope.”

Meta did not provide detailed information on how much AI-generated disinformation its fact-checking uncovered related to major elections.

Source:: Computer World

Apple shops at Amazon.

In this case, it is using artificial intelligence (AI) processors from Amazon Web Services (AWS) for some of its Apple Intelligence and other services, including Maps, Apps, and search. Apple is also testing advanced AWS chips to pretrain some of its AI models as it continues its rapid pivot toward becoming the world’s most widely deployed AI platform.

That’s the big — and somewhat unexpected — news to emerge from this week’s AWS:Reinvent conference.

Apple watchers will know that the company seldom, if ever, sends speakers to other people’s trade shows. So, it matters that Apple’s Senior Director of Machine Learning and AI, Benoit Dupin, took to the stage at the Amazon event. That appearance can be seen as a big endorsement both of AWS and its AI services, and the mutually beneficial relationship between Apple and AWS.

Not a new relationship.

Apple has used AWS servers for years, in part to drive its iCloud and Apple One services and to scale additional capacity at times of peak demand. “One of the unique elements of Apple’s business is the scale at which we operate, and the speed with which we innovate. AWS has been able to keep the pace,” Dupin said.

Some might note that Dupin (who once worked at AWS) threw a small curveball when he revealed that Apple has begun to deploy Amazon’s Graviton and Inferentia for machine learning services such as streaming and search. He explained that moving to these chips has generated an impressive 40% efficiency increase in Apple’s machine learning inference workloads when compared to x86 instances. 

Dupin also confirmed Apple is in the early stages of evaluating the newly-introduced AWS Trainium 2 AI training chip, which he expects will bring in 50% improvement in efficiency when pre-training AI. 

Scale, speed, and Apple Intelligence

On the AWS connection to Apple Intelligence, he explained: “To develop Apple Intelligence, we needed to further scale our infrastructure for training.” As a result, Apple turned to AWS because the service could provide access to the most performant accelerators in quantity. 

Dupin revealed that key areas where Apple uses Amazon’s services include fine-tuning AI models, optimizing trained models to fit on small devices, and “building and finalizing our Apple Intelligence adapters, ready to deploy on Apple devices and servers.. We work with AWS Services across virtually all phase of our AI and ML lifecycle,” he said. 

Apple Intelligence is a work in progress and the company is already developing additional services and feature improvements, “As we expand the capabilities and feature of Apple Intelligence, we will continue to depend on the scalable, efficient, high-performance accelerator technologies AWS delivers,” he said. 

Apple CEO Tim Cook recently confirmed more services will appear in the future. “I’m not going to announce anything today. But we have research going on. We’re pouring all of ourselves in here, and we work on things that are years in the making,” Cook said.

TSMC, Apple, AWS, AI, oh my!

There’s another interesting connection between Apple and AWS. Apple’s M- and A- series processors are manufactured by Taiwan Semiconductor Manufacturing (TSMC), with devices made by Foxconn and others. TSMC also makes the processors used by AWS. And it manufactures the AI processors Nvidia provides; we think it will be tasked with churning out Apple Silicon server processors to support Private Cloud Compute services and Apple Intelligence.

It is also noteworthy that AWS believes it will be able to link more of its processors together for huge cloud intelligence servers beyond what Nvidia can manage. Speaking on the fringes of AWS Reinvent, AWS AI chip business development manager Gadi Hutt claimed his company’s processors will be able to train some AI models at 40% lower cost than on Nvidia chips. 

Up next?

While the appearance of an Apple exec at the AWS event suggests a good partnership, I can’t help but be curious about whether Apple has its own ambitions to deliver server processors, and the extent to which these might deliver significant performance/energy efficiency gains, given the performance efficiency of Apple silicon.

Speculation aside, as AI injects itself into everything, the gold rush for developers capable of building and maintaining these services and the infrastructure (including energy infrastructure) required for the tech continues to intensify; these kinds of fast-growing industry-wide deployments will surely be where opportunity shines.

You can watch Dupin’s speech here.

You can follow me on social media! Join me on BlueSky,  LinkedIn, Mastodon, and MeWe. 

Source:: Computer World

By Siôn Geschwindt Google Deepmind researchers have built an AI weather forecasting tool that makes faster and more accurate predictions than the best system available today. Dubbed GenCast, the new model outperformed the ENS forecast, widely regarded as the world leader, 97% of the time for predictions up to 15 days in advance. It was tested on over 1,320 weather scenarios, including tropical cyclones and heatwaves. “Outperforming ENS marks something of an inflection point in the advance of AI for weather prediction,” Ilan Price, a research scientist at Google DeepMind, told the Guardian. “At least in the short term, these models are going…This story continues at The Next WebOr just read more coverage about: Google

Source:: The Next Web

By Deepti Pathak Multiplication is one of the most common tasks in spreadsheets, and Google Sheets makes it easy…
The post How To Multiply in Google Sheets? appeared first on Fossbytes.

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By Deepti Pathak Google Slides isn’t just for presentations; it’s also a creative tool. Drawing can make your content…
The post How to Draw on Google Slides? appeared first on Fossbytes.

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By Nick Godt Hyundai remains committed to offering CarPlay and Android Auto, the in-car phone-mirroring apps.

Source:: Digital Trends

By Siôn Geschwindt UK startup PhysicsX, founded by former Formula 1 engineering whizz Robin “Dr. Rob” Tuluie, has unveiled an AI tool that could fast-track the time it takes to design a new aircraft from months to just a few days.  Dubbed LGM-Aero, the software creates new designs for aeroplanes. Using advanced algorithms trained on more than 25 million geometries, the model predicts lift, drag, stability, structural stress and other attributes for each shape. It then tailors the design according to what you want your plane to do. PhysicsX said the AI is the first-ever Large Geometry Model (LGM) for aerospace engineering. A…This story continues at The Next Web

Source:: The Next Web

According to a new report from the Organization for Economic Co-operation and Development (OECD), generative AI (genAI) will soon affect work areas previously considered to have a low likelihood of automation, according to The Register.

Automation in the past mainly affected industrial jobs in rural areas. GenAI, on the other hand, can be used for non-routine cognitive tasks, which is expected to affect more highly skilled workers and big cities where these workers are often based. The report estimates that up to 70% of these workers will be able to get half of their tasks done twice as fast with the help of genAI. The industries likely to be affected include education, IT, and finance.

The OECD notes that even if work tasks disappear, unemployment won’t necessarily increase. The overall number of jobs could increase, but those new positions might not directly benefit those who lost work because of automation and new efficiencies.

Source:: Computer World

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Source:: Computer World