Tools & Platforms
Is Massachusetts keeping pace with the AI technology race?
A new report out today looks at the strengths of various U.S. cities when it comes to funding, research, job creation and usage of AI technologies, and finds two California cities in the lead: San Francisco and San Jose.
That’s not a huge surprise, as those two cities are generally considered the northern and southern poles of the Silicon Valley region, which is home to companies such as OpenAI, Google, Elon Musk’s X.ai, Anthropic and Stanford University.
But Boston is ranked among 27 other metropolitan areas as a “star hub,” according to the new report from the Brookings Institution, a nonpartisan think tank based in Washington, D.C.
Those cities all have “strong AI ecosystems, balancing top‑tier talent, research and enterprise uptake” of AI software, according to the report. However, the report notes that just as the state government in Massachusetts has created a new AI hub to foster more development in the industry, so have states such as New York, New Jersey and North Dakota.
Boston scores best in the new report on factors related to our universities and our ability to pull in federal funding. We’re #1 when it comes to our population of workers with doctorates in computer science, math or engineering; #1 when it comes to cranking out research papers related to AI and #2 when it comes to attracting federal research dollars related to Research and Development (The report, incidentally, relies on data about federal funding from 2024, before President Trump took office and initiated significant cuts.)
“Federal investment cuts could be very damaging, especially to less developed areas, but also to Greater Boston,” said Mark Muro, a senior fellow at the Brookings Institution who co-authored the report, “Mapping the AI Economy.” “We think maintaining federal research flows, especially in the face of what China is doing, is very important — for the nation, and for excellent local clusters like Boston’s. The same goes for immigrant talent and foreign students.”
I sought out reactions to the report from a handful of people active in the Boston AI scene.
“Being ranked second-tier feels a bit like getting a B+ on a test you studied hard for — good effort, but you know you’ve got an A in you,” wrote Jonathan Corbin via email.
Corbin is chief executive of Maven AGI, a Boston AI startup that serves corporate customers.
“Boston attracts and generates talent from schools like Harvard, MIT and Babson, but where it falls behind is in the investments to help people stay here and build” their companies, he wrote.
Rudina Seseri of Glasswing Ventures is a venture capitalist who frequently backs AI startups. She said, “I would like to see greater investment in compute infrastructure accessible to startups and researchers, faster commercialization pathways for AI research coming out of our universities and more targeted workforce development programs — especially those that broaden access beyond traditional tech pipelines.”
Seseri added that “we would also benefit enormously from incentives to attract AI investment dollars and make it easier for local startups to pilot and scale their technologies.”
“Boston doesn’t need to copy Silicon Valley, we need to be a louder version of ourselves,” said Judah Phillips, the Boston-based Chief AI and Product Officer of Market Holdings, a New Jersey company. Among the ideas he suggests: more capital and tax incentives to grow companies here, as well as integrating AI into K-12 education, and “more apprenticeships and credential programs to give more people access to real AI jobs.”
He would also like to see the state of Massachusetts invest in AI technology from startups.
Phillips is an organizer of Boston AI Week, taking place this fall, which includes a career fair he helped start in 2024. Their goal is to organize 100 different events over the course of the week.
Paul Baier, an AI analyst who is also involved with Boston AI Week, said that “Boston has plenty of assets.” But he said that after the passage of the Mass Leads economic development bill in 2024, which proposed creating an AI Hub, “momentum seems to have slowed. I hope with the appointments of a new Secretary of Economic Development and Executive Director of the AI Hub that communications and speed increase.”
A spokesperson for the AI Hub, part of the Massachusetts Technology Collaborative, a public economic development agency primarily funded by the state, said the hub plans to spend about $50 million over the next two fiscal years.
Among its initiatives: a professional development program for high school science and technology educators, and an “AI Models Innovation Challenge” to “encourage ethical, impactful and forward-looking advancements in applied AI,” according to spokesperson Jake Stern.
The Brookings Institution report touches on the impact AI will have on jobs — especially white-collar professions. Research from Brookings suggests that roughly one-third of all workers “could see at least 50% of their occupation’s tasks disrupted by generative AI in the coming years, with higher ‘exposure’ levels for higher-skill computer and office activities,” according to the report.
Some of that disruption could create new jobs and enhance productivity, the report says, but it could also lead to “chronic under- or unemployment.”
“For sure, the nation will want to invest more in ‘active labor market policies’ that help people shift into new jobs,” the report says. This could include funding for retraining workers, as well as developing more flexible benefits that are not tied to a single employer.
Other data released this week on venture capital funding for startups also finds that funding for AI companies in California — and in particular, money raised by ChatGPT-maker OpenAI, is helping to increase that state’s funding totals, while venture capital in Massachusetts declined in the second quarter of 2025, dropping to its lowest level in eight years.
That’s not a great sign, since funding is a key ingredient for growing future crops of successful companies.
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Tools & Platforms
China’s top social media platforms take steps to comply with new AI content labeling rules
China’s top social media platforms, including ByteDance Ltd.’s TikTok clone Douying and Tencent Holdings’ WeChat, rolled out new features today to try to comply with a new law that mandates all artificial intelligence content is clearly labeled as such.
The new content labeling rules mandate that all AI-generated content posted on social media is tagged with explicit markings visible to users. It applies to AI-generated text, images, videos and audio, and also requires that implicit identifiers, such as digital watermarks, are embedded in the content’s metadata.
The law, which was first announced in March by the Cyberspace Administration of China, reflects Beijing’s increased scrutiny of AI at a time when concerns are rising about misinformation, online fraud and copyright infringement.
According to a report in the South China Morning Post, the law comes amid a broader push by Chinese authorities to increase oversight of AI, as illustrated by the CAC’s 2025 Qinglang campaign, which aims to clean up the Chinese language internet.
WeChat, one of the most popular messaging platforms in China, which boasts more than 1.4 billion monthly active users globally, has said that all creators using its platform must voluntarily declare any AI-generated content they publish. It’s also reminding users to “exercise their own judgement” for any content that has not been flagged as AI generated.
In a post today, WeChat said it “strictly prohibits” any attempts to delete, tamper with, forge or conceal AI labels added by its own automated tools, which are designed to pick up any AI-generated content that’s not flagged by users who upload it. It also reminded users against using AI to spread false information or for any other “illegal activities.”
Meanwhile Douyin, which has around 766 million monthly active users, said in a post today that it’s encouraging users to add clear labels to every AI-generated video they upload to its platform. It will also attempt to flag AI-generated content that isn’t flagged by users by checking its source via its metadata.
Several other popular social media platforms made similar announcements. For instance, the microblogging site Weibo, often known as China’s Twitter, said on Friday it’s adding tools for users to tag their own content, as well as a button for users to report “unlabeled AI content” posted by others.
RedNote, the e-commerce-based social media platform, issued its own statement on Friday, saying that it reserves the right to add explicit and implicit identifiers to any unidentified AI-generated content it detects on its platform.
Many of China’s best known AI tools are also moving to comply with the new law. For instance, Tencent’s AI chatbot Yuanbao said on Sunday it has created a new labeling system for any content it generates on behalf of users, adding explicit and implicit tags to text, videos and images. In its statement, it also advised users that they should not attempt to remove the labels it automatically adds to the content it creates.
When the CAC announced the law earlier this year, it said its main objectives were to implement robust AI content monitoring, enforce mandatory labeling and apply penalties to anyone who disseminates misinformation through AI or uses the technology to manipulate public opinion. It also pledged to crack down on deceptive marketing that uses AI, and strengthen online protections for underage users.
The European Union is set to implement its own AI content labeling requirements in August 2026, as part of the EU AI Act, which mandates that any content “significantly generated” by AI must be labeled to ensure transparency. The U.S. has not yet mandated AI content labels, but a number of social media platforms, such as Meta Platforms Inc., are implementing their own policies regarding the tagging of AI-generated media.
Photo: WeChat
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Nvidia dropped solidly by -3.32%, with the trading volume of 42.33B. UAE AI company G42 is seeking to diversify its chip supply beyond Nvidia, including negotiations with tech giants like Amazon AWS, Google, Meta, Microsoft, and xAI for its planned AI park. Google is reportedly leading in these discussions.
2. Tesla (Nasdaq: TSLA)
Tesla dropped solidly by -3.50%, with the trading volume of 27.32B. Tesla’s CEO Elon Musk states that 80% of Tesla’s value will depend on the Optimus robot. Despite challenges in Europe, including executive resistance and competition, Tesla lowered Model 3 prices in China, marking its long-range version’s debut with a price cut.
3. Alibaba Group Holding Limited (NYSE: BABA)
Alibaba Group Holding Limited surged by 12.90%, with the trading volume of 10.94B. Alibaba plans to invest over 380 billion yuan in the next three years to boost its computing power industry, impacting domestic AI infrastructure. Its Q1 FY 2026 financial report showed a 10% revenue growth and a 76% net profit increase, exceeding expectations.
4. Microsoft (Nasdaq: MSFT)
Microsoft dipped mildly by -0.58%, with the trading volume of 10.63B. UAE AI company G42 is diversifying chip supplies to reduce dependency on Nvidia, engaging with tech giants like Amazon AWS, Google, Meta, Microsoft, and Elon Musk’s xAI for a planned AI park, with Google’s negotiations being the most advanced.
5. Apple (Nasdaq: AAPL)
Apple dipped mildly by -0.18%, with the trading volume of 9.16B. Apple is expanding its retail footprint in India with a new store, Apple Hebbal, set to open in Bangalore on September 2. This follows the openings of Apple BKC in Mumbai and Apple Saket in Delhi. Apple also plans to remove physical SIM card slots in more countries for the iPhone 17 series.
6. Alphabet (Nasdaq: GOOGL)
Alphabet gained mildly by 0.60%, with the trading volume of 8.44B. UAE’s AI company G42 is seeking to diversify its chip suppliers to reduce reliance on Nvidia. They are negotiating with major tech companies including Amazon AWS, Google, Meta, Microsoft, and Elon Musk’s xAI, with Google likely to sign a computing power procurement deal soon.
7. Palantir Technologies (NYSE: PLTR)
Palantir Technologies dipped mildly by -0.89%, with the trading volume of 7.27B. South Korean retail investors showed significant interest in Palantir Technologies, with substantial net purchases over the past week.
8. Meta Platforms (Nasdaq: META)
Meta Platforms dipped mildly by -1.65%, with the trading volume of 6.70B. Meta and Scale AI’s partnership faced challenges as major investment leads to strained relations and data quality concerns. Additionally, Meta plans to release a smart glasses SDK, diverging from trends by opting for LCoS over Micro LED technology.
9. Broadcom (Nasdaq: AVGO)
Broadcom dropped solidly by -3.65%, with the trading volume of 6.42B. Broadcom (AVGO.US) is expected to report a 21% revenue increase to $15.82 billion for Q3, with EPS projected at $1.66. Oppenheimer reaffirmed its “outperform” rating, raising the target price to $325. The AI business could exceed $5 billion in revenue.
10. Marvell Technology (Nasdaq: MRVL)
Marvell Technology plunged by -18.60%, with the trading volume of 6.19B. Company XYZ announced plans for global expansion, focusing on emerging markets and sustainable initiatives. New partnerships aim to enhance technological capabilities, while leadership emphasizes innovation and growth potential.
A new JD Pwoer study reveals which AI features drivers actually love and which ones are still frustratingly confusing
31 minutes ago
- Owners are proving particularly receptive to smart climate control systems.
- Genesis took out top honors for innovation for the fifth consecutive year.
- There is also growing demand from buyers for in-car payment systems.
Artificial intelligence has been steadily weaving its way into everyday life, from the phones in our pockets to the services we rely on daily. The auto industry has been no exception, and AI-driven features are now shaping how people interact with their cars.
Α new study from J.D. Power has found that while some of these features are being well-received by consumers, there are many others that need work before they actually start adding to the ownership experience.
Read: JLR Is Now Using The AI Damage Scanners That Hertz Customers Hate
As part of an expansion of its annual U.S. Tech Experience Index (TXI) Study, J.D. Power looked at seven AI-based technologies that should, in theory, enhance the driving experience. Among them, one of the clear successes is smart climate control, which automatically manages heating, ventilation, and air conditioning to balance comfort and efficiency.
Smarter Comfort in Action
The study found that owners using these systems are now reporting 6.3 fewer problems per 100 vehicles (PP100) than before, a meaningful improvement. These systems also provide a much-needed workaround for the growing number of cars that have moved climate settings into touchscreen menus instead of physical buttons. J.D. Power’s broader studies back this up, noting that smart climate controls are now boosting both vehicle quality scores and customer satisfaction overall.
Other AI-based systems are also showing promise, such as smart ignition and driver preference modes. In-vehicle shopping and payment systems also drew attention, with 62 percent of owners expressing interest. So far, the most common uses are paying for fuel, tolls, parking, or EV charging, but past designs have struggled with clunky menus and limited apps.
According to the study, the next generation could succeed if automakers focus on simple, quick purchases tied directly to the driving experience.
Blind spot cameras stand out as one of the most appreciated technologies, with 93 percent of drivers saying they use them regularly and 74 percent wanting the feature in their next vehicle. Models equipped with blind spot cameras also tend to sell faster than those without, underlining just how valuable the technology has become.
Features That Miss the Mark
By comparison, several other AI features could be improved. For example, J.D. Power concluded that car wash modes becoming increasingly prevalent across the market have lots of room for improvement. These models automatically prepare a vehicle to go through a car wash, but it was found that this mode is often buried within the infotainment system, and 38 percent of owners say they need better instructions on how to use it.
Similar, recognition technologies remain a sticking point, posting the highest problem rates in the study. Biometric authentication alone averaged more than 29 issues per 100 vehicles, while touchless or hidden controls and direct driver monitoring each saw more than 19.
Which Brands Are The Best For Tech?
The study also compared automakers on their overall use of technology. Genesis once again led the pack, taking the top spot for the fifth year in a row, with Cadillac and Lincoln following behind.
The premium segment’s average score was lifted to 671 with Tesla and Rivian included, but both were excluded from the rankings since they did not meet the study’s award criteria. Even so, Tesla posted a standout score of 873 and Rivian followed with 730, according to J.D. Power.
In the mass-market category, Hyundai claimed the highest score for innovation, followed by Kia and, perhaps more surprisingly, Mitsubishi, which ranked ahead of GMC, MINI, and Toyota.
At the other end of the spectrum, Stellantis brands such as Jeep, Ram, and Chrysler landed at the bottom, while Jaguar held the lowest position among premium marques. And if you’re wondering about Tesla, while giving it a huge score at 873, JD Power said it
JD Power
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