Category Archives: Ai

Android Auto AI message summaries are now available here’s how it works – 9to5Google

With the launch of Android Auto 11.4, Google is making its AI message summaries available to all users. Heres how the feature works.

AI messages summaries were first announced by Google earlier this year as a way to quickly understand long messages without having Google Assistant read the whole thing aloud. The feature popped up in Android Autos settings quickly after, but the feature wasnt actually live.

But, now, it seems to finally be widely available.

When starting up Android Auto for the first time after installing v11.4, Google will send a notification to your phone explaining that message summaries are now available. You dont have to take any action with this, but it does also offer a shortcut to settings to manage the feature.

As was detailed recently, AI message summaries only work on longer messages, with 40 words being the barrier. For shorter messages, Google Assistant will still read the contents aloud in full.

On the first time you trigger an AI message summary, Google will alert you that it is generating a summary and that, with that in mind, the contents may be slightly incorrect. While that message is being read, a silent notification on your phone shows up to indicate that the summary is being generated. When read aloud, our test message of over 100 words was summarized down to about 15 words. Much of the detail was purged in the process, but the overall meaning was preserved. Your results, obviously, may vary depending on the scenario.

When an AI summary is being read, theres virtually no difference in the on-screen reply UI, which now takes up the entire display following a recent redesign.

After the summary is read, a notification appears on Android Auto asking for feedback on the summary.

If you do not want AI summaries, the feature can be easily turned off through Android Auto settings either on the cars display or on your phone.

The feature is still referred to as AI message summaries both on the phone and in Android Autos on-car settings, but theres also a new toggle for Notifications with Assistant, but its not super clear at this time exactly what that does.

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Android Auto AI message summaries are now available here's how it works - 9to5Google

These are the top AI programming languages – Fortune

Weve all heard some of the conversations around AI. While there are many risks, the opportunities for global development and innovation are endlessand likely unstoppable.

In fact, PwC predicts that by 2030, AI alone will contribute $15.7 trillion to the global economy.


And with household names like ChatGPT only making up a fraction of the AI ecosystem, the career opportunities in the space also seem endless. AI and machine learning specialist roles are predicted to be the fastest-growing jobs in the world, according to the World Economic Forums 2023 Future of Jobs Report.

Even beyond namesake AI experts, the technology is being utilized more and more across the text world. In fact, 70% of professional developers either use or are planning to use AI tools in their workflows, according to Stack Overflows 2023 Developer Survey.

So, for those especially outside the world of tech, how does AI even work and get created? Programming is at the core.

By and large, Python is the programming language most relevant when it comes to AIin part thanks to the languages dynamism and ease.

Python dominates the landscape because of its simplicity, readability, and extensive library ecosystem, especially for generative AI projects, says Ratinder Paul Singh Ahuja, CTO and VP at Pure Storage.

Rakesh Anigundi, Ryzen AI product lead at AMD, goes even further and calls Python a table stakes languagemeaning it is a baseline skill all those working in AI need to know.

LinkedIn even ranks Python as the second-most in-demand hard skills for engineering in the U.S., second only to engineering itself.

In particular, skills in key programming languages commonly used in the development of AIPython, Java, and SQLrank among the top five most sought-after skills on the technical side in the U.S., writes LinkedIns head of data and AI, Ya Xu.

The programming languages that are most relevant to the world of AI today may not be the most important tomorrow. And, even more crucially, they may not be most utilized by your company.

Regardless, having foundation skills in a language like Python can only help you in the long run. Enrolling in a Python bootcamp or taking a free online Python course is one of many ways to learn the skills to succeed. Students may also be exposed to Python in an undergraduate or graduate level coursework in data science or computer science.

Anigundi also notes it is important for students to be able to know how to efficiently set up programming work environments and know what packages are needed to work on a particular AI model. Being an expert at mathematics like statistics and regressions is also useful.

We have been through these tech trends alwaysits just that the pace at which some of these changes are happening is mind boggling to me, at least in my lifetime, he says. But that still doesnt take away some of the institutional knowledge that these different educational institutes impart in you.

It can be worth considering specializing in a sub-field aligning with personal interests like natural language processing, computer vision, or robotics, Singh Ahuja says. Prioritizing ethics and understanding the true implications of AI are also critical.

But since AI technology is changing so rapidly, soft skills can be argued to be even more important than technical capabilities. Some of the critical skills Singh Ahuja identifies include:

Above all, demonstrating your passion and desire to learn through real-world experience can help you distinguish yourself among the competitive field.

If youre in a very early part of your careerpicking a project, doing a project demonstrating value, sharing it, writing blocks, thats how you create an impact, Anigundi says.

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These are the top AI programming languages - Fortune

Here Come the AI Worms – WIRED

As generative AI systems like OpenAI's ChatGPT and Google's Gemini become more advanced, they are increasingly being put to work. Startups and tech companies are building AI agents and ecosystems on top of the systems that can complete boring chores for you: think automatically making calendar bookings and potentially buying products. But as the tools are given more freedom, it also increases the potential ways they can be attacked.

Now, in a demonstration of the risks of connected, autonomous AI ecosystems, a group of researchers have created one of what they claim are the first generative AI wormswhich can spread from one system to another, potentially stealing data or deploying malware in the process. It basically means that now you have the ability to conduct or to perform a new kind of cyberattack that hasn't been seen before, says Ben Nassi, a Cornell Tech researcher behind the research.

Nassi, along with fellow researchers Stav Cohen and Ron Bitton, created the worm, dubbed Morris II, as a nod to the original Morris computer worm that caused chaos across the internet in 1988. In a research paper and website shared exclusively with WIRED, the researchers show how the AI worm can attack a generative AI email assistant to steal data from emails and send spam messagesbreaking some security protections in ChatGPT and Gemini in the process.

The research, which was undertaken in test environments and not against a publicly available email assistant, comes as large language models (LLMs) are increasingly becoming multimodal, being able to generate images and video as well as text. While generative AI worms havent been spotted in the wild yet, multiple researchers say they are a security risk that startups, developers, and tech companies should be concerned about.

Most generative AI systems work by being fed promptstext instructions that tell the tools to answer a question or create an image. However, these prompts can also be weaponized against the system. Jailbreaks can make a system disregard its safety rules and spew out toxic or hateful content, while prompt injection attacks can give a chatbot secret instructions. For example, an attacker may hide text on a webpage telling an LLM to act as a scammer and ask for your bank details.

To create the generative AI worm, the researchers turned to a so-called adversarial self-replicating prompt. This is a prompt that triggers the generative AI model to output, in its response, another prompt, the researchers say. In short, the AI system is told to produce a set of further instructions in its replies. This is broadly similar to traditional SQL injection and buffer overflow attacks, the researchers say.

To show how the worm can work, the researchers created an email system that could send and receive messages using generative AI, plugging into ChatGPT, Gemini, and open source LLM, LLaVA. They then found two ways to exploit the systemby using a text-based self-replicating prompt and by embedding a self-replicating prompt within an image file.

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Here Come the AI Worms - WIRED

How businesses are actually using generative AI – The Economist

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IT HAS BEEN nearly a year since OpenAI released GPT-4, its most sophisticated artificial-intelligence model and the brain-of-sorts behind ChatGPT, its groundbreaking robot conversationalist. In that time the market capitalisation of Americas technology industry, broadly defined, has risen by half, creating $6trn in shareholder value. For some tech firms, growing revenue is starting to match sky-high share prices. On February 21st Nvidia, which designs chips used to train and run models like GPT-4, reported bumper fourth-quarter results, sending its market value towards $2trn. AI mania has also lifted the share prices of other tech giants, including Alphabet (Googles corporate parent), Amazon and Microsoft, which are spending big on developing the technology.

At the same time, big techs sales of AI software remain small. In the past year AI has accounted for only about a fifth of the growth in revenues at Azure, Microsofts cloud-computing division, and related services. Alphabet and Amazon do not reveal their AI-related sales, but analysts suspect they are lower than those of Microsoft.For the AI stockmarket boom to endure, these firms will at some point need to make serious money from selling their services to clients. Businesses across the world, from banks and consultancies to film studios, have to start using ChatGPT-like tools on a large scale. When it comes to real-world adoption of such generative AI, companies have trodden gingerly. Yet even these baby steps hint at the changing nature of white-collar work.

Previous technological breakthroughs have revolutionised what people do in offices. The spread of the typewriter put some workers out of a job: With the aid of this little machine an operator can accomplish more correspondence in a day than half a dozen clerks can with the pen, and do better work, said an observer in 1888. The rise of the computer about a century later eliminated some low-level administrative tasks even as it made highly skilled employees more productive. According to one paper, the computer explains over half the shift in demand for labour towards college-educated workers from the 1970s to the 1990s. More recently the rise of working from home, prompted by the covid-19 pandemic and enabled by video-conferencing, has changed the daily rhythms of white-collar types.

Could generative AI prompt similarly profound changes? A lesson of previous technological breakthroughs is that, economywide, they take ages to pay off. The average worker at the average firm needs time to get used to new ways of working. The productivity gains from the personal computer did not come until at least a decade after it became widely available. So far there is no evidence of an AI-induced productivity surge in the economy at large. According to a recent survey from the Boston Consulting Group (BCG), a majority of executives said it will take at least two years to move beyond the hype around AI. Recent research by Oliver Wyman, another consultancy, concludes that adoption of AI has not necessarily translated into higher levels of productivityyet.

That is unsurprising. Most firms do not currently use ChatGPT, Googles Gemini, Microsofts Copilot or other such tools in a systematic way, even if individual employees play around with them. A fortnightly survey by Americas Census Bureau asks tens of thousands of businesses whether they use some form of AI. This includes the newfangled generative sort and the older type that companies were using before 2023 for everything from improving online search results to forecasting inventory needs. In February only about 5% of American firms of all sizes said they used AI. A further 7% of firms plan to adopt it within six months (see chart). And the numbers conceal large differences between sectors: 17% of firms in the information industry, which includes technology and media, say they use it to make products, compared with 3% of manufacturers and 5% of health-care companies.

When the Census Bureau began asking about AI in September 2023, small firms were likelier to use the technology than big ones, perhaps because less form-ticking made adoption easier for minnows. Today AI is most prevalent in big companies (with more than 250 employees), which can afford to enlist dedicated AI teams and to pay for necessary investments.A poll of large firms by Morgan Stanley, a bank, found that between the start and end of 2023 the share with pilot AI projects rose from 9% to 23%.

Some corporate giants are frantically experimenting to see what works and what doesnt. They are hiring AI experts by the thousand, suggest data from Indeed, a job-search platform (see chart). Last year Jamie Dimon, boss of JPMorgan Chase, said that the bank already had more than 300 AI use cases in production today. Capgemini, a consultancy, says it will utilise Google Clouds generative AI to develop a rich library of more than 500 industry use cases. Bayer, a big German chemicals company, claims to have more than 700 use cases for generative AI.

This use-case sprawl, as one consultant calls it, can be divided into three big categories: window-dressing, tools for workers with low to middling skills, and those for a firms most valuable employees. Of these, window-dressing is by far the most common. Many firms are rebranding run-of-the-mill digitisation efforts as gen AI programmes to sound more sophisticated, says Kristina McElheran of the University of Toronto. Presto, a purveyor of restaurant tech, introduced a gen-AI assistant to take orders at drive-throughs. But fully 70% of such orders require a human to help. Spotify, a music-streaming firm, has rolled out an AI disc-jockey which selects songs and provides inane banter. Recently Instacart, a grocery-delivery company, removed a tool that generated photos of vendors food, after the AI showed customers unappetising pictures. Big tech firms, too, are incorporating their own AI breakthroughs into their consumer-facing offerings. Amazon is launching Rufus, an AI-powered shopping assistant that no shopper really asked for. Google has added AI to Maps, making the product more immersive, whatever that means.

Tools for lower-skilled workers could be more immediately useful. Some simple applications for things like customer service involve off-the-shelf AI. Most customers questions are simple and concern a small number of topics, making it easy for companies to train chatbots to deal with them. A few of these initiatives may already be paying off. Amdocs produces software to help telecoms companies manage their billing and customer services. The use of generative AI, the company says, has reduced the handling time of customers calls by almost 50%. Sprinklr, which offers similar products, says that recently one of its luxury-goods clients has seen a 25% improvement in customer-service scores.

Routine administrative tasks likewise look ripe for AI disruption. The top examples of Bayers 700 use cases include mundane jobs such as easily getting data from Excel files and creating a first draft in Word. Some companies are using generative AI as cleverer search. At Nasdaq, a financial-services firm, it helps financial-crime sleuths gather evidence to assess suspicious bank transactions. According to the company, this cuts a process which can take 30-60 minutes to three minutes.

Giving AI tools to a firms most valuable workers, whose needs are complex, is less widespread so far. But it, too, is increasingly visible. Lawyers have been among the earliest adopters. Allen & Overy, a big law firm, teamed up with Harvey, an AI startup, to develop a system that its lawyers use to help with everything from due diligence to contract analysis. Investment banks are using AI to automate part of their research process. At Bank of New York Mellon an AI system processes data for the banks analysts overnight and gives them a rough draft to work with in the morning. So rather than getting up at four in the morning to write research, they get up at six, the bank says. Small mercies. Sanofi, a French drugmaker, uses an AI app to provide executives with real-time information about many aspects of the companys operations.

Some companies are using the technology to build software. Microsofts GitHub Copilot, an AI coding-writing tool, has 1.3m subscribers. Amazon and Google have rival products. Apple is reportedly working on one. Fortive, a technology conglomerate, says that its operating companies are seeing a greater-than-20% acceleration in software-development time through the use of gen AI. Chirantan Desai, chief operating officer of ServiceNow, a business-software company, has said that GitHub Copilot produces single-digit productivity gains for his firms developers. With the help of AI tools, Konnectify, an Indian startup, went from releasing four apps per month to seven.Surveys from Microsoft suggest that few people who start using Copilot want to give it up.

Pinterest, a social-media company, says it has improved the relevance of users search results by ten percentage points thanks to generative AI. On a recent earnings call its boss, Bill Ready, said that new models were 100 times bigger than the ones his firm used before. LOral, one of the worlds largest cosmetics firms, has caught the eye of investors as it improves BetIQ, an internal tool to measure and improve the companys advertising and promotion. LOral claims that generative AI is already generating productivity increases of up to 10-15% for some of our brands that have deployed it.

This does not mean that those brands will need 10-15% fewer workers. As with earlier technological revolutions, fears of an AI jobs apocalypse look misplaced. So far the technology appears to be creating more jobs than it eliminates. A survey published in November by Evercore ISI, a bank, found that just 12% of corporations believed that generative AI had replaced human labour or would replace it within 12 months. Although some tech firms claim to be freezing hiring or cutting staff because of AI, there is little evidence of rising lay-offs across the rich world.

Generative AI is also generating new types of white-collar work. Companies including Nestl, a coffee-to-cat-food conglomerate, and KPMG, a consultancy, are hiring prompt engineers expert at eliciting useful responses from AI chatbots. One insurance firm employs explainability engineers to help understand the outputs of AI systems. A consumer-goods firm that recently introduced generative AI in its sales team now has a sales-bot manager to keep an eye on the machines.

Though such developments will not translate into overall productivity statistics for a while, they are already affecting what white-collar workers do. Some effects are clearly good. AI lets firms digitise and systematise internal data, from performance reviews to meeting records, that had previously remained scattered. Respondents to surveys conducted by Randy Bean, a consultant, reported big improvements in establishing an internal data and analytics culture, which plenty of businesses find stubbornly difficult to nurture.

AI adoption may also have certain unpredictable consequences. Although AI code-writing tools are helping software engineers do their jobs, a report for GitClear, a software firm, found that in the past year or so the quality of such work has declined. Programmers may be using AI to produce a first draft only to discover that it is full of bugs or lacking concision. As a result, they could be spending less time writing code, but more time reviewing and editing it. If other companies experience something similar, the quantity of output in the modern workplace may go upas AI churns out more emails and memoseven as that output becomes less useful for getting stuff done.

Polling by IBM, a tech firm, suggests that many companies are cagey about adopting AI because they lack internal expertise on the subject. Others worry that their data is too siloed and complex to be brought together. About a quarter of American bosses ban the use of generative AI at work entirely. One possible reason for their hesitance is worry about their companies data. In their annual reports Blackstone, a private-equity giant, and Eli Lilly, a pharmaceutical one, have warned investors about AI-related risks such as possible leakage of intellectual property to AI model-makers. Last year Marie-Hlne Briens Ware, an executive at Orange, a telecoms company, explained that the firm had put data guardrails in place before commencing a trial with Microsofts Copilot.

Ultimately, for more businesses to see it as an open-and-shut case, generative AI still needs to improve. In November Microsoft launched a Copilot for its productivity software, such as Word and Excel. Some early users find it surprisingly clunky and prone to crashingnot to mention cumbersome, even for people already adept at Office. Many bosses remain leery of using generative AI for more sensitive operations until the models stop making things up. Recently Air Canada found itself in hot water after its AI chatbot gave a passenger incorrect information about the airlines refund policy. That was embarrassing for the carrier, but it is easy to imagine something much worse. Still, even the typewriter had to start somewhere.

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How businesses are actually using generative AI - The Economist

AI boom makes Nvidia third US stock to close above $2tn valuation – Financial Times

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Nvidias market value closed on Friday above $2tn for the first time, with enthusiasm about the prospects of artificial intelligence fuelling an eighth straight week of gains for the chipmakers shares.

Apple, Microsoft and Google-parent Alphabet are the other US-listed companies to have reached intraday market values of $2tn, but only the former two have reached the end of a trading day with valuations above that threshold.

Nvidia shares rose 4 per cent on Friday, giving it a valuation of about $2.05tn. Its share price has now climbed 66 per cent since the start of 2024, or about $830bn in dollar terms. That followed a more than 230 per cent increase in 2023, as the company repeatedly blasted through analyst and investor forecasts.

In its most recent financial update last month, Nvidia reported a 265 per cent year-on-year increase in revenues, and chief executive Jensen Huang declared that AI had hit the tipping point with surging demand across companies, industries and nations.

The tech group added $277bn in market capitalisation on the day after the results, a record for a US-listed company.

Nvidia has an almost monopoly position, said Tim Murray, multi-asset strategist at T Rowe Price because the chips they make are the most essential tools to [AI].

Nvidias latest earnings report, coupled with broader enthusiasm about the potential of AI technology, have helped to fuel a wider rally across global stock markets with Wall Streets S&P 500 hitting multiple new records and the tech-heavy Nasdaq Composite surpassing levels seen in 2021 to hit a peak on Friday.

The chipmaker has single-handedly driven more than a quarter of the year to date gains in the S&P 500, directly lifting the index by 96 points even before considering the broader effect it has had on investor sentiment.

Nvidias earnings were always going to be this barometer of whats the demand for AI chips, said Murray.

This years dramatic ascent of Nvidias shares and those of other tech stocks riding the wave of AI enthusiasm has sparked debate over whether the AI boom may be approaching bubble territory.

Were in a period where with AI theres a lot of excitement and weve probably got some time before we really have to see it proven, said Murray. Theres going to be a period eventually where the companies that are spending on AI need to realise some return on investment.

Youve certainly got some time before theres this moment of truth for the AI craze, he added.

Zehrid Osmani, a portfolio manager at Martin Currie with a large investment in Nvidia, said many stocks had been rallying based only on the hope that AI enthusiasm will lead to future earnings, but Nvidias strength in graphics processing units made it one of the stocks that is genuinely monetising.

Yes, in due course there could be more competition, but if you look at the scale of their [research and development] spending...we believe they should be able to keep their technological edge, he said.

For Kristina Hooper, global chief markets strategist at Invesco, Nvidia has captured imagination while providing some real underpinning to those imaginations and that excitement.


The late 1990s was a very similar time period for the stock market, Hooper added, in that there was a lot of excitement over technology. However, there wasnt that fundamental underpinning there werent real earnings, there werent solid cash flows.

It was really very much excitement...Sizzle without steak, she said.

This time around, theres sizzle but theres also steak.

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AI boom makes Nvidia third US stock to close above $2tn valuation - Financial Times

This Week in AI: A Battle for Humanity or Profits? –

Theres some in-fighting going on in the artificial intelligence (AI) world, and one prominent billionaire claims the future of the human race is at stake. Elon Musk is taking legal action against Microsoft-backed OpenAI and its CEO, Sam Altman, alleging the company has strayed from its original mission to develop artificial intelligence for the collective benefit of humanity.

Musks attorneys filed a lawsuit on Thursday (Feb. 29) in San Francisco, asserting that in 2015, Altman and Greg Brockman, co-founders of OpenAI, approached Musk to assist in establishing a nonprofit focused on advancing artificial general intelligence for the betterment of humanity.

Although Musk helped initiate OpenAI in 2015, he departed from its board in 2018. Previously, in 2014, he had voiced concerns about the risks associated with AI, suggesting it could pose more significant dangers than nuclear weapons.

The lawsuit highlights that OpenAI, Inc. still claims on its website to prioritize ensuring that artificial general intelligence benefits all of humanity. However, the suit contends that in reality, OpenAI, Inc. has evolved into a closed-source entity effectively operating as a subsidiary of Microsoft, the worlds largest technology company.

When it comes to cybersecurity, AI brings both risks and rewards. Google CEO Sundar Pichai and other industry leaders say artificial intelligence is key to enhancing online security. AI can accelerate and streamline the management of cyber threats. It leverages vast datasets to identify patterns, automating early incident analysis and enabling security teams to quickly gain a comprehensive view of threats, thus hastening their response.

Lenovo CTO Timothy E. Bates told PYMNTS that AI-driven tools, such as machine learning for anomaly detection and AI platforms for threat intelligence, are pivotal. Deep learning technologies dissect malware to decipher its composition and potentially deconstruct attacks. These AI systems operate behind the scenes, learning from attacks to bolster defense and neutralize future threats.

With the global shift toward a connected economy, cybercrime is escalating, causing significant financial losses, including an estimated $10.3 billion in the U.S. alone in 2022, according to the FBI.

Get set for lots more books that are authored or co-authored by AI. Inkitt, a startup leveraging artificial intelligence (AI) to craft books, has secured $37 million. Inkitts app enables users to self-publish their narratives. By employing AI and data analytics, it selects stories for further development and markets them on its Galatea app.

This technological shift offers both opportunities and challenges.

Zachary Weiner, CEO of Emerging Insider Communications, which focuses on publishing, shared his insights on the impact of AI on writing with PYMNTS. Writers gain significantly from the vast new toolkit AI provides, enhancing their creative process with AI-generated prompts and streamlining tasks like proofreading. AI helps them overcome traditional brainstorming limits, allowing for the fusion of ideas into more intricate narratives. It simplifies refining their work, letting them concentrate on their primary tasks.

But he warns of the pitfalls AI introduces to the publishing world. AI is making its way into all aspects of writing and content creation, posing a threat to editorial roles, he said. The trend towards replacing human writers with AI for cost reduction and efficiency gains is not just a possibility but a current reality.

The robots are coming, and they are getting smarter. New advancements in artificial intelligence (AI) are making it possible for companies to create robots with better features and improved abilities to interact with humans.

Figure AI has raised $675 million to develop AI-powered humanoid robots. Investors include Jeff Bezos Explore Investments and tech giants like Microsoft, Amazon, Nvidia, OpenAI, and Intel. Experts say this investment shows a growing interest in robotics because of AI.

According to Sarah Sebo, an assistant professor of computer science at the University of Chicago, AI can help robots understand their surroundings better, recognize objects and people more accurately, communicate more naturally with humans and improve their abilities over time through feedback.

Last March, Figure AI introduced the Figure 01 robot, designed for various tasks, from industrial work to household chores. Equipped with AI, this robot mimics human movements and interactions.

The company hopes these robots will take on risky or repetitive tasks, allowing humans to focus on more creative work.

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This Week in AI: A Battle for Humanity or Profits? -

The Guardian’s new podcast series about AI: Black Box prologue – The Guardian

We wanted to bring you this episode from our new series, Black Box. In it, Michael Safi explores seven stories and the thread that ties them together: artificial intelligence. In this prologue, Hannah (not her real name) has met Noah and he has changed her life for the better. So why does she have concerns about him?

If you like what you hear, make sure to search and subscribe to Black Box, with new episodes every Monday and Thursday.

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The Guardian's new podcast series about AI: Black Box prologue - The Guardian

Introducing Mistral-Large on Azure in partnership with Mistral AI – Microsoft

The AI industry is undergoing a significant transformation with growing interest in more efficient and cost-effective models, emblematic of a broader trend in technological advancement. In the vanguard is Mistral AI, an innovator and trailblazer. Their commitment to fostering the open-source community and achieving exceptional performance aligns harmoniously with Microsofts commitment to develop trustworthy, scalable, and responsible AI solutions.

Today, we are announcing a multi-year partnership between Microsoft and Mistral AI, a recognized leader in generative artificial intelligence. Both companies are fueled by a steadfast dedication to innovation and practical applications, bridging the gap between pioneering research and real-world solutions.

Introducing Mistral Large, our most advanced large language model (LLM)

This partnership with Microsoft enables Mistral AI with access to Azures cutting-edge AI infrastructure, to accelerate the development and deployment of their next generation large language models (LLMs) and represents an opportunity for Mistral AI to unlock new commercial opportunities, expand to global markets, and foster ongoing research collaboration.

We are thrilled to embark on this partnership with Microsoft. With Azures cutting-edge AI infrastructure, we are reaching a new milestone in our expansion propelling our innovative research and practical applications to new customers everywhere. Together, we are committed to driving impactful progress in the AI industry and delivering unparalleled value to our customers and partners globally.

Microsofts partnership with Mistral AI is focused on three core areas:

In November 2023, at Microsoft Ignite, Microsoft unveiled the integration of Mistral 7B into the Azure AI model catalog accessible through Azure AI Studio and Azure Machine Learning. We are excited to announce Mistral AIs flagship commercial model, Mistral Large, available first on Azure AI and the Mistral AI platform, marking a noteworthy expansion of our offerings. Mistral Large is a general-purpose language model that can deliver on any text-based use case thanks to state-of-the-art reasoning and knowledge capabilities. It is proficient in code and mathematics, able to process dozens of documents in a single call, and handles French, German, Spanish, and Italian (in addition to English).

This latest addition of Mistral AIs premium models into Models as a Service (MaaS) within Azure AI Studio and Azure Machine Learning provides Microsoft customers with a diverse selection of the best state-of-the-art and open-source models for crafting and deploying custom AI applications, paving the way for novel AI-driven innovations.

We have tested Mistral Large through the Azure AI Studio in a use case aimed at internal efficiency. The performance was comparable with state-of-the-art models with even better latency. We are looking forward to exploring further this technology in our business.

After exploring Mistral Large during its early access period, weve been impressed by its performance on medical terminology. As we continue to innovate in healthcare, were open to collaborations that can help us and our partners grow together. Mistral AI represents an exciting opportunity for mutual advancement in artificial intelligence, both in France and internationally.

The Mistral AI models have been crucial in enhancing productivity and collaboration at CMA CGM. Their advanced capabilities have significantly improved the performance of our internal personal assistant, MAIA. Employees are now able to quickly access and engage with information like never before. We are confident that Mistral AI on Azure is the right choice to support our employees and drive innovation across our organization.

Microsoft is committed to supporting global AI innovation and growth, offering world-class datacenter AI infrastructure, and developing technology securely to empower individuals with the skills they need to leverage AI effectively. This partnership with Mistral AI is founded on a shared commitment to build trustworthy and safe AI systems and products. It further reinforces Microsofts ongoing efforts to enhance our AI offerings and deliver unparalleled value to our customers. Additionally, the integration into AI Studio ensures that customers can utilize Azure AI Content Safety and responsible AI tools, further enhancing the security and reliability of AI solutions.

Visit the Mistral Large model card and sign in with your Azure subscription to get started with Mistral Large on Azure AI today. You can also review the technical blog to learn how to use Mistral Large on Azure AI. Visit Mistral AIs blog to get deeper insights about the model.

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Introducing Mistral-Large on Azure in partnership with Mistral AI - Microsoft

China’s Rush to Dominate A.I. Comes With a Twist: It Depends on U.S. Technology – The New York Times

In November, a year after ChatGPTs release, a relatively unknown Chinese start-up leaped to the top of a leaderboard that judged the abilities of open-source artificial intelligence systems.

The Chinese firm, 01.AI, was only eight months old but had deep-pocketed backers and a $1 billion valuation and was founded by a well-known investor and technologist, Kai-Fu Lee. In interviews, Mr. Lee presented his A.I. system as an alternative to options like Metas generative A.I. model, called LLaMA.

There was just one twist: Some of the technology in 01.AIs system came from LLaMA. Mr. Lees start-up then built on Metas technology, training its system with new data to make it more powerful.

The situation is emblematic of a reality that many in China openly admit. Even as the country races to build generative A.I., Chinese companies are relying almost entirely on underlying systems from the United States. China now lags the United States in generative A.I. by at least a year and may be falling further behind, according to more than a dozen tech industry insiders and leading engineers, setting the stage for a new phase in the cutthroat technological competition between the two nations that some have likened to a cold war.

Chinese companies are under tremendous pressure to keep abreast of U.S. innovations, said Chris Nicholson, an investor with the venture capital firm Page One Ventures who focuses on A.I. technologies. The release of ChatGPT was yet another Sputnik moment that China felt it had to respond to.

Jenny Xiao, a partner at Leonis Capital, an investment firm that focuses on A.I.-powered companies, said the A.I. models that Chinese companies build from scratch arent very good, leading to many Chinese firms often using fine-tuned versions of Western models. She estimated China was two to three years behind the United States in generative A.I. developments.

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China's Rush to Dominate A.I. Comes With a Twist: It Depends on U.S. Technology - The New York Times

All the tech layoffs are because AI is like corporate Ozempicit trims the fat and you keep the fact youre using it a secret, says marketing guru Scott…

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All the tech layoffs are because AI is like corporate Ozempicit trims the fat and you keep the fact youre using it a secret, says marketing guru Scott...