Then on the other extreme, [the left-wing New Popular Front] have been so vocal about all the taxation measures they want to bring back that it looks like we're just going back to pre-Macron period, Varza says. She points to Frances 2012 les pigeons (or suckers) movement, a campaign by angry internet entrepreneurs that opposed Socialist president Franois Hollandes plan to dramatically raise taxes for founders.

Maya Nol, CEO of France Digitale, an industry group for startups, is worried not only about Frances ability to attract overseas talent, but also about how appealing the next government will be to foreign investors. In February, Google said it would open a new AI hub in Paris, where 300 researchers and engineers would be based. Three months later, Microsoft also announced a record $4 billion investment in its French AI infrastructure. Meta has had an AI research lab in Paris since 2015. Today France is attractive to foreign investors, she says. And we need them. Neither Google nor Meta replied to WIREDs request for comment. Microsoft declined to comment.

The vote will not unseat Macron himselfthe presidential election is not scheduled until 2027but the election outcome could dramatically reshape the lower house of the French Parliament, the National Assembly, and install a prime minister from either the far-right or left-wing coalition. This would plunge the government into uncertainty, raising the risk of gridlock. In the past 60 years, there have been only three occasions when a president has been forced to govern with a prime minister from the opposition party, an arrangement known in France as cohabitation.

No AI startup has benefited more from the Macron era than Mistral, which counts Cdric O, former digital minister within Macrons government, among its cofounders. Mistral has not commented publicly on the choice France faces at the polls. The closest the company has come to sharing its views is Cdric Os decision to repost an X post by entrepreneur Gilles Babinet last week that said: I hate the far-right but the lefts economic program is surreal. When WIRED asked Mistral about the retweet, the company said O was not a spokesperson, and declined to comment.

Babinet, a member of the governments artificial intelligence committee, says he has already heard colleagues considering leaving France. A few of the coders I know from Senegal, from Morocco, are already planning their next move, he says, claiming people have also approached him for help renewing their visas early in case this becomes more difficult under a far-right government.

While other industries have been quietly rushing to support the far-right as a preferable alternative to the left-wing alliance, according to reports, Babinet plays down the threat from the New Popular Front. It's clear they come with very old-fashioned economical rules, and therefore they don't understand at all the new economy, he says. But after speaking to New Popular Front members, he says the hard-left are a minority in the alliance. Most of these people are Social Democrats, and therefore they know from experience that when Franois Hollande came into power, he tried to increase the taxes on the technology, and it failed miserably.

Already there is a sense of damage control, as the industry tries to reassure outsiders everything will be fine. Babinet points to other moments of political chaos that industries survived. At the end of the day, Brexit was not so much of a nightmare for the tech scene in the UK, he says. The UK is still the preferred place to launch a generative AI startup, according to the Accel report.

Stanislas Polu, an OpenAI alumnus who launched French AI startup Dust last year, agrees the industry has enough momentum to survive any headwinds coming its way. Some of the outcomes might be a bit gloomy, he says, adding he expects personal finances to be hit. Its always a little bit more complicated to navigate a higher volatility environment. I guess were hoping that the more moderate people will govern that country. I think thats all we can hope for.

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French AI Startups Felt Unstoppable. Then Came the Election - WIRED

Instagrams new AI Studio will let creators make AI chatbot versions of themselves, and Meta is starting to roll it out as an early test in the US, CEO Mark Zuckerberg announced on his broadcast channel on Thursday.

As part of the test, you might start seeing AIs from your favorite creators and interest-based AIs in the coming weeks on Instagram, according to Zuckerberg. These will primarily show up in messaging for now, and will be clearly labeled as AI.

Zuckerberg shared a few videos of conversations with creator-made AI chatbots as examples. From a creators Instagram, you can tap a Message button to kick off a conversation. A notice at the top says that the messages are generated by AI and some may be inaccurate or inappropriate. (Lets hope Metas systems can prevent these creator-made AIs from saying something terrible.) Meta also includes AI in front of the creators name and, at least for now, a beta tag after the persons name.

Weve been working closely with creators to build these so theyre helpful in answering the questions they get from their followers and can chat with people in a way thats useful and fun, Zuckerberg says. Its early days and the first beta version of these AIs so well keep working on improving them, and make them available to more people soon.

In a new interview, Zuckerberg talked more about the companys AI strategy. He says, We think people want to interact with lots of different people and businesses and there need to be a lot of different AIs that get created to reflect peoples different interests. Meta wants to let creators and eventually small businesses create an AI for themselves to interact with their communities and customers. We think thats going to create a much more compelling experience and just be more dynamic and useful than just having a single thing that people use. He also says Meta will let people make AI characters that arent necessarily representations of themselves.

Broadly, this is a vision the company has had for a while Zuckerberg made similar remarks in an interview with my colleague Alex Heath last year when the company announced its Meta AI assistant and celebrity-themed chatbots. Now that the company is actually testing AI Studio, well see if people really do want to chat with AI versions of their favorite creators.

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Instagram is starting to let some creators make AI versions of themselves - The Verge

Since the release of ChatGPT in November 2022, educators have pondered its implications for education. Some have leaned toward apocalyptic projections about the end of learning, while others remain cautiously optimistic.

My students took longer than I expected to discover generative AI. When I asked them about ChatGPT in February 2023, many had never heard of it.

But some caught up, and now our colleges academic integrity office is busier than ever dealing with AI-related cheating. The need for guidelines is discussed in every college meeting, but Ive noticed a worrying reaction among students that educators are not considering: fear.

Students are bombarded with negative ideas about AI. Punitive policies heighten that fear while failing to recognize the potential educational benefits of these technologies and that students will need to use them in their careers. Our role as educators is to cultivate critical thinking and equip students for a job market that will use AI, not to intimidate them.

Yet course descriptions include bans on the use of AI. Professors tell students they cannot use it. And students regularly read stories about their peers going on academic probation for using Grammarly. If students feel constantly under suspicion, it can create a hostile learning environment.

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Many of my students havent even played around with ChatGPT because they are scared of being accused of plagiarism. This avoidance creates a paradox in which students are expected to be adept with these modern tools post-graduation, yet are discouraged from engaging with them during their education.

I suspect the profile of my students makes them more prone to fear AI. Most are Hispanic and female, taking courses in translation and interpreting. They see that the overwhelmingly male and white tech bros in Silicon Valley shaping AI look nothing like them, and they internalize the idea that AI is not for them and not something they need to know about. I wasnt surprised that the only male student I had in class this past semester was the only student excited about ChatGPT from the very beginning.

Failing to develop AI literacy among Hispanic students can diminish their confidence and interest in engaging with these technologies. Their fearful reactions will widen the already concerning inequities between Hispanic and non-Hispanic students; the degree completion gap between Latino and white students increased between 2018 and 2021.

The stakes are high. Similar to the internet boom, AI will revolutionize daily activities and, certainly, knowledge jobs. To prepare our students for these changes, we need to help them understand what AI is and encourage them to explore the functionalities of large language models like ChatGPT.

I decided to address the issue head-on. I asked my students to write speeches on a current affairs topic. But first, I asked for their thoughts on AI. I was shocked by the extent of their misunderstanding: Many believed that AI was an omniscient knowledge-producing machine connected to the internet.

After I gave a brief presentation on AI, they expressed surprise that large language models are based on prediction rather than direct knowledge. Their curiosity was piqued, and they wanted to learn how to use AI effectively.

After they drafted their speeches without AI, I asked them to use ChatGPT to proofread their drafts and then report back to me. Again, they were surprised this time about how much ChatGPT could improve their writing. I was happy (even proud) to see they were also critical of the output, with comments such as It didnt sound like me or It made up parts of the story.

Was the activity perfect? Of course not. Prompting was challenging. I noticed a clear correlation between literacy levels and the quality of their prompts.

Students who struggled with college-level writing couldnt go beyond prompts such as Make it sound smoother. Nonetheless, this basic activity was enough to spark curiosity and critical thinking about AI.

Individual activities like these are great, but without institutional support and guidance, efforts toward fostering AI literacy will fall short.

The provost of my college established an AI committee to develop college guidelines. It included professors from a wide range of disciplines (myself included), other staff members and, importantly, students.

Through multiple meetings, we brainstormed the main issues that needed to be included and researched specific topics like AI literacy, data privacy and safety, AI detectors and bias.

We created a document divided into key points that everyone could understand. The draft document was then circulated among faculty and other committees for feedback.

Initially, we were concerned that circulating the guidelines among too many stakeholders might complicate the process, but this step proved crucial. Feedback from professors in areas such as history and philosophy strengthened the guidelines, adding valuable perspectives. This collaborative approach also helped increase institutional buy-in, as everyones contribution was valued.

Related: A new partnership paves the way for greater use of AI in higher ed

Underfunded public institutions like mine face significant challenges integrating AI into education. While AI offers incredible opportunities for educators, realizing these opportunities requires substantial institutional investment.

Asking adjuncts in my department, who are grossly underpaid, to find time to learn how to use AI and incorporate it into their classes seems unethical. Yet, incorporating AI into our knowledge production activities can significantly boost student outcomes.

If this happens only at wealthy institutions, we will widen academic performance gaps.

Furthermore, if only students at wealthy institutions and companies get to use AI, the bias inherent in these large language models will continue to grow.

If we want our classes to ensure equitable educational opportunities for all students, minority-serving institutions cannot fall behind in AI adoption.

Cristina Lozano Argelles is an assistant professor of interpreting and bilingualism at John Jay College, part of the City University of New York, where she researches the cognitive and social dimensions of language learning.

This story about AI literacy was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for Hechingers newsletter.

The Hechinger Report provides in-depth, fact-based, unbiased reporting on education that is free to all readers. But that doesn't mean it's free to produce. Our work keeps educators and the public informed about pressing issues at schools and on campuses throughout the country. We tell the whole story, even when the details are inconvenient. Help us keep doing that.

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TEACHER VOICE: My students are afraid of AI - The Hechinger Report

OpenAIs abrupt move to ban access to its services in China is setting the scene for an industry shakeup, as local AI leaders from Baidu Inc. to Alibaba Group Holding Ltd. move to grab more of the field.

The ChatGPT creator this week sent memos to Chinese users warning it will cut off access to its widely used AI development software and tools from July, triggering a scramble to fill the void. Since Tuesday, at least a half-dozen companies and startups including Tencent Holdings Ltd. and Zhipu AI began offering incentives to developers making the switch.

OpenAIs shift will accentuate the divide between China and the U.S., which is trying to curb Beijings AI and chip efforts. While the startups exit offers an opportunity for sector leaders to grow their user base, it also deprives entrepreneurs and cash-strapped startups of some of the best tools available to fine-tune or get their AI applications off the ground.

Read More: OpenAI Says Russia, China, and Israel Are Using Its Tools for Foreign Influence Campaigns

For China, that could help usher out many smaller startups created during the battle of a hundred models, in the wake of ChatGPTs late 2022 debut. And a bigger concern may be whether open-source models like Meta Platforms Inc.s Llama also cut off access, said Bernard Leong, chief executive officer of Singapore-based Dorje AI.

Theres probably going to be a bloodbath of the large language models and I suspect that theres probably going to be very few players left, said Leong, whos also founder of the tech podcast Analyse Asia. There will be very few winners, and those will be the biggest in China.

Chinese artificial intelligence-related stocks, including Alibaba and Iflytek Co., rose on Wednesday.

The major firms were quick to sense the opportunity.

For users migrating from OpenAI, Baidu promised free AI model fine-tuning and expert guidance on its flagship Ernie model, along with 50 million free tokens that developers can use to query the bot. Alibaba and Tencent posted ads encouraging the shift. Tech pioneer Kai-fu Lees 01.AI touted heavy discounts.

Baichuan, which is backed by both Alibaba and Tencent,offered10 million free tokens. SenseTime Group Inc.dangled50 million. Zhipu put forth 150 million tokens and a series of training sessions to ease the transition. Even Microsoft Corp. OpenAIs biggest backer published a step-by-step guide onWeChaton how to migrate to its local service, operated by local partner 21Vianet.

U.S. firms such as OpenAI, Meta and Alphabet Inc. have led the world in generative AI, which spits out text, images and video from simple commands. Underpinning those models are application programming interfaces that developers use to build up and refine their own platforms to integrate services either with the likes of ChatGPT, or their own proprietary models.

Read More: Gen AI Has Already Taken the World by Storm. Just Wait Until It Gets a Quantum Boost

That was a boon to Chinese developers starting from scratch, who accessed OpenAIs tools through virtual private networks or other ways around the countrys Great Firewall. Many local developers particularly those without deep pockets favored training AI systems and applications via OpenAIs tools, because they were regarded as industry benchmarks.

OpenAI is now threatening to sever the connection.

Leading Chinese large language models can benefit from the restricted access to OpenAI, and it will help to filter out smaller, less effective players from the market, said You Chuanman, head of the Chinese University of Hong Kong-Shenzhens IIA Centre for Regulation and Global Governance. At the same time, it will make it harder for Chinese developers to use the most advanced global AI algorithms.

OpenAIs move coincides with rising pressure from Washington to curb Chinese access to the most advanced artificial intelligence and semiconductor technology. The U.S. Treasury Department advanced plans over the weekend to further restrict investments by U.S. individuals and companies into China, with a focus on curtailing next-generation technologies.

In the long run, industry experts say a lack of access to global tools may further impede Chinese AI players in general as they play catch-up to the US. Alibaba Chairman Joe Tsai has said it would take at least two years for homegrown AI models to match U.S. ones.

It could also accelerate a migration overseas by Chinese tech startups seeking faster-growing markets with less political uncertainty.

This situation is directly related to the ongoing competition between China and the U.S. in frontier technologies, said Neil Zhu Xiaohu, the founder and chief scientist of University AI, which trains Chinese companies.

We had U.S. laws targeting Chinese semiconductors previously and more recently, there are semiconductor and AI work restrictions, so the restriction of Chinas API services is not something that happened out of the blue.

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How OpenAI Leaving China Will Reshape the Country's AI Scene - TIME

Nvidia will remain the gold standard for AI training chips, CEO Jensen Huang told investors, even as rivals push to cut into his market share and one of Nvidias major suppliers gave a subdued forecast for AI chip sales.

Everyone from OpenAI to Elon Musks Tesla rely on Nvidia semiconductors to run their large language or computer vision models. The rollout of Nvidias Blackwell system later this year will only cement that lead, Huang said at the companys annual shareholder meeting on Wednesday.

Unveiled in March, Blackwell is the next generation of AI training processors to follow its flagship Hopper line of H100 chipsone of the most prized possessions in the tech industry fetching prices in the tens of thousands of dollars each.

The Blackwell architecture platform will likely be the most successful product in our history and even in the entire computer history, Huang said.

Nvidia briefly eclipsed Microsoft and Apple this month to become the worlds most valuable company in a remarkable rally that hasfueledmuch of this years gains in theS&P 500 index. At more than $3 trillion, Huangs company was at one point worth more than entire economies andstock markets, only to suffer arecord loss in market valueas investors locked in profits.

Yet as long as Nvidia chips continue to be the benchmark for AI training, theres little reason to believe thelonger-term outlookis cloudy, and here thefundamentalscontinue to look robust.

One of Nvidias key advantages is a sticky AI ecosystemknown as CUDA, short for Compute Unified Device Architecture. Much like how everyday consumers are loath to switch from their Apple iOS device to a Samsung phone using Google Android, an entire cohort of developers have been working with CUDA for years and feel so comfortable that there is little reason to consider using another software platform. Much like the hardware, CUDA effectively has become a standard of its own.

The Nvidia platform is broadly available through every major cloud provider and computer maker, creating a large and attractive base for developers and customers, which makes our platform more valuable to our customers, Huang added on Wednesday.

The AI trade did take a recent hit after memory-chip supplier Micron Technology, provider of high-bandwidth memory (HBM) chips to companies like Nvidia, forecast fiscal fourth-quarter revenue would only match market expectations of around $7.6 billion.

Shares in Micron plunged 7%, underperforming by a large margin a slight gain in the broader tech-heavy Nasdaq Composite.

In the past, Micron and its Korean rivals Samsung and SK Hynix have seen a cyclical boom-and-bust common to the memory-chip market, long considered a commodity business when compared with logic chips such as graphic processors.

But excitement has surged given the demand for its chips necessary for AI training. Microns stock more than doubled over the past 12 months, meaning investors have already priced in much of managements predicted growth.

The guidance was basically in line with expectations, and in the AI hardware world if you guide in line thats considered a slight disappointment, says Gene Munster, a tech investor with Deepwater Asset Management. Momentum investors just didnt see that incremental reason to be more positive about the story.

Analysts closely track demand for high-bandwidth memory as a leading indicator for the AI industry because it is so crucial for solving the biggest economic constraint facing AI training todaythe issue of scaling.

Costs crucially do not rise in line with a models complexitythe number of parameters it has, which can number into the billionsbut rather grow exponentially. This results in diminishing returns in efficiency over time.

Even if revenue grows at a consistent rate, losses risk ballooning into the billions or even tens of billions a year as a model gets more advanced. This threatens to overwhelm any company that doesnt have a deep-pocketed investor like Microsoft capable of ensuring an OpenAI can still pay the bills, as CEO Sam Altman phrased it recently.

A key reason for diminishing returns is the growing gap between the two factors that dictate AI training performance. The first is a logic chips raw compute poweras measured by FLOPS, a type of calculation per secondand the second is the memory bandwidth needed to quickly feed it dataoften expressed in millions of transfers per second, or MT/s.

Since they work in tandem, scaling one without the other simply leads to waste and cost inefficiency. Thats why FLOPS utilization, or how much of the compute can actually be brought to bear, is a key metric when judging the cost efficiency of AI models.

As Micronpoints out, data transfer rates have been unable to keep pace with rising compute power. The resulting bottleneck, often referred to as the memory wall is a leading cause for todays inherent inefficiency when scaling AI-training models.

That explains why theU.S. government focused heavily onmemory bandwidthwhen deciding which specific Nvidia chips needed to be banned from export to China in order to weaken Beijings AI development program.

On Wednesday, Micron said its HBM business was sold out all the way through the end of the next calendar year, which trails its fiscal year by one quarter, echoingsimilar commentsfrom Korean competitor SK Hynix.

We expect to generate several hundred million dollars of revenue from HBM in FY24 and multiple [billions of dollars] in revenue from HBM in FY25, Micron said on Wednesday.

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Nvidia's Jensen Huang plays down competition worries as key supplier disappoints with subdued expectations for AI ... - Fortune