After ChatGPT and other large language models were released, people online started raising concerns about data privacy. Some even suggested stopping all new data from being used to train these models — but that would seriously limit what AI can do in the future.
Luckily, there’s a better way. AI can still be trained without using personal data. This method is called federated learning, and in this article, we’ll explore what it is and how it could shape the future of AI training.
Routing Model Updates Through Proxy Servers for Extra Privacy and Speed
Federated learning involves devices training a shared model on their own data and then sending model updates (like learned parameters or gradients) to be aggregated into a global model. One emerging enhancement is to route these model updates through proxy servers or intermediary nodes instead of directly to the central aggregator. This added indirection can significantly bolster privacy by anonymizing which device contributed which update, effectively ensuring client anonymity.
Using a proxy server can also improve the speed and efficiency of federated learning. For instance, a proxy can gather and compress updates from many devices before forwarding them, cutting down on communication overhead. Research on “ProxyFL” – a proxy-based federated learning scheme – found that communicating via proxies not only strengthened privacy (especially when combined with techniques like differential privacy) but also reduced bandwidth usage and latency in training.
By offloading some coordination duties to proxy nodes (which might be located closer to client devices or handle partial aggregations), federated networks can train faster and scale to more participants. The main idea is that sending updates through trusted proxies adds extra protection for user data and makes learning more efficient — all without raw data ever leaving the users’ devices.
Federated Learning vs. Centralized Learning: How It Works
In the traditional method, all the training data is sent to one central server or cloud, where the model is trained. This means users or organizations have to transfer their original data to one place, which can obviously cause privacy issues and other problems.
Federated learning flips that paradigm. Instead of bringing data to the model, FL brings the model to the data. The initial model (often just a starting point with random or pre-trained weights) is sent out from the server to many devices (phones, IoT gadgets, or organizational servers). The server then aggregates these updates (e.g. by averaging them) to improve the global model, which can be sent back to devices in iterative rounds. Crucially, your personal data stays on your device – the server only sees the learned patterns, which are usually far less sensitive than the raw data.
This decentralized training approach was first introduced by Google researchers in 2016, originally to train smartphone models like the Android keyboard predictor. In fact, Google and Apple have famously used federated learning to train keystroke prediction models on millions of smartphones without ever collecting users’ actual typing data. By training on-device, Google’s Gboard and Apple’s QuickType keyboards can improve suggestions using what people type, while the sensitive text messages never leave the phones.
Apple has extended the idea to other areas as well – for example, Apple’s Health app uses federated learning to analyze usage patterns of health data types across users’ devices while maintaining each user’s privacy. This means the Health app can learn which health metrics or exercises are most popular or effective, collectively, without Apple seeing any individual’s personal health logs.
Beyond consumer apps, federated learning is transforming how organizations collaborate on AI. A notable case study comes from the healthcare sector: Intel and the University of Pennsylvania led a federated learning pilot involving 29 medical institutes around the world to jointly train an AI model for brain tumor detection. None of the hospitals shared their patient data with each other or with Intel; instead, each hospital trained the model on its own MRI scans and then shared model updates.
The combined model learned from a much larger, diverse dataset than any single hospital could provide. In other words, by using FL the researchers nearly matched the performance of traditional training while adhering to patient privacy constraints. So, federated learning provided a way to access vastly more data (spread across hospitals) while protecting the security of that data – a win-win for both model performance and privacy.
Source link
#Federated #Learning #Explained #Devices #Train #Handing #Data
![This former notorious red-light district is now one of the world’s top AI hubs | TechCrunch
What every U.K. AI startup wants to know these days is, how can I get office space in King’s Cross?
The area is so hot that a VC firm allegedly recently won a deal by promising a founder office space in the neighborhood. “We stop at nothing to win deals [for] and to support” founders, “including helping them source office space when needed,” the firm told me when asked about the rumor, declining to confirm or deny any details.
The neighborhood’s popularity began back in 2016 when DeepMind — then newly acquired by Google — moved in. Soon after, a flood of AI startups followed, wanting to be around the Google DeepMind magic. Today, they hope to take advantage of the cluster of AI talent there.
This has transformed King’s Cross into one of the world’s top AI hubs, rivaled only by San Francisco and Beijing. Around London, it’s known by the sobriquet “Knowledge Quarter,” as it’s home to names like OpenAI, Meta, Isomorphic Labs, Cusp AI, Wayne, Recursive, and, a little farther down the road, Synthesia and Anthropic. The European Technology Network (ETN) just moved into a glossy new office nearby, while University College London sits around the corner.
Mixed in with the new developments are trendy food spots like Hoppers and BAO. Hop a train from King’s Cross, and founders can be in Cambridge in 45 minutes to source talent or can be in Paris in two hours to strike a deal.
Who would have guessed that a little more than 20 years ago, this was one of the seediest areas in London?
“In the ’80s, crack and heroin made the area a major narcotics market,” Hussein Kanji, an investor at Hoxton Ventures, said, recalling syringes in tree trunks and gangs patrolling the streets. “In 1982, the local church was occupied by the English Collective of Prostitutes for 12 straight days.” Then, in the early 2000s, a real estate developer had a dream and, well, “now it is the AI hotbed of the United Kingdom,” Kanji said. “What a change.” Around 18 months ago, his portfolio company BioCorteX moved from the neighborhood Holborn to the Jellicoe building in King’s Cross, hoping to be near the action. “Lots going on in London right now,” Nik Sharma, co-founder of BioCorteX, told me. “Lots of hyperscalers moving in.” That includes, reportedly, Jeff Bezos’ AI company Prometheus, which is also said to be in talks to move into the Jellicoe.
There are around 3,600 AI startups in London, which, together, have raised around .1 billion out of the .8 billion raised in the city since late July, according to Dealroom. Since the start of June, AI-related startups have leased more than 1 million square feet of office space in London, according to the real estate firm Knight Frank. With that, prime rents in King’s Cross have risen 18% over the past three years, Chris Dunn, a commercial insight associate at the firm, told me. That percentage represents only the largest leases encompassing at least 10,000 square feet, like the ones OpenAI and Prometheus are signing. The shorter deals go for even more, he said, and now the vacancy rate for conventional office space is just 0.9%. “Demand has outstripped supply,” he continued.
Today, one of the big topics of the area is sovereignty. It was a wake-up call for many when Anthropic shut off access to Mythos and Fable this summer, leaving some in the ecosystem to conclude: “We’d better look after ourselves,” Saul Klein, co-founder of the VC firm Phoenix Court, told me.
Phoenix Court is located in the King’s Cross area and has three portfolio companies in the vicinity, including Olix (which just announced a .3 billion valuation), Early Health and CoMind. Robin Klein, co-founder of the firm, said the shutdown of Fable and Mythos access was a “small but sharp reminder that Europe can’t simply rent its AI capabilities and capacity; it needs to build and hold some of its own.” King’s Cross, he said, is where much of this building is actually happening.
“The bigger question,” he continued, “is whether the U.K. builds the infrastructure, compute, energy, capital, to make this self-reliance durable, rather than just hosting outposts of U.S. labs.”
Image Credits:Phoenix Court
Top founders want to stay
Simon Kohl, founder of Latent Labs, has offices in King’s Cross and San Francisco. The London office, at the moment, is growing faster, and he’s more bullish than ever on the ecosystem, he said. “The mood right now feels less like London trying to catch up and more like London becoming one of the default places to start a serious AI company,” he said. Look around and you are likely to see Wayve testing its autonomous cars. Founded in 2017 by co-founder Alex Kendall, the unicorn is one of London’s biggest success stories.
“Ten years ago, building a frontier AI company from London felt like an unusual choice,” Kendall told me. “Now it feels like an obvious one.” Wayve moved into King’s Cross in 2018 looking for a space that could double as a garage — “a rare combination in Central London,” Kendall said. He has watched the ecosystem mature around him — and it’s now evident that a startup can stay in London, raise serious capital, hire world-class AI talent, and remain globally competitive, he said. Down the street from Anthropic’s new 158,000-square-foot office is the AI agent builder Sierra and the AI video platform Synthesia.
Laura Gonzalez Florez, Synthesia’s chief of staff and head of people, says the company moved into its glossy new office building a year ago to accommodate its growing team. They were drawn to the area for the same reason as everyone else: “It’s very close to the airport … very close to where a lot of investors are,” she said.
Image Credits:Synthesia
Around two-thirds of Synthesia’s engineers are remote, Gonzalez Florez said, letting the company tap into an affordable, international, and diverse talent pool and helping it scale faster. “From London, we can hire and work, without any problem, people from anywhere, from Slovenia to Portugal,” she said.
Unsurprisingly, London’s AI boom is also causing a talent war.U.K. AI job postings have skyrocketed in the past few years, per data from PwC. When Anthropic announced it moved into town earlier this year, it listed, for example, a salary range of £260,000 to £630,000 for a machine learning research engineer when the average salary in London for the same role is around £102,000. Some founders in the U.K., like those in Silicon Valley, are being forced to raise more and bigger rounds to keep up.
“The real test is whether more globally significant AI companies are founded, funded, and scaled from the U.K., while continuing to attract the world’s best talent to build them here,” Zain Ali, founder of the King’s Cross-based AI legal firm Centuro, told me. “If that continues to happen, King’s Cross won’t just be an AI hub. It’ll become one of the U.K.’s most important strategic assets.”
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Thisformernotorious #redlight #districtis #nowone #worlds #top #hubs #TechCrunchUK This former notorious red-light district is now one of the world’s top AI hubs | TechCrunch
What every U.K. AI startup wants to know these days is, how can I get office space in King’s Cross?
The area is so hot that a VC firm allegedly recently won a deal by promising a founder office space in the neighborhood. “We stop at nothing to win deals [for] and to support” founders, “including helping them source office space when needed,” the firm told me when asked about the rumor, declining to confirm or deny any details.
The neighborhood’s popularity began back in 2016 when DeepMind — then newly acquired by Google — moved in. Soon after, a flood of AI startups followed, wanting to be around the Google DeepMind magic. Today, they hope to take advantage of the cluster of AI talent there.
This has transformed King’s Cross into one of the world’s top AI hubs, rivaled only by San Francisco and Beijing. Around London, it’s known by the sobriquet “Knowledge Quarter,” as it’s home to names like OpenAI, Meta, Isomorphic Labs, Cusp AI, Wayne, Recursive, and, a little farther down the road, Synthesia and Anthropic. The European Technology Network (ETN) just moved into a glossy new office nearby, while University College London sits around the corner.
Mixed in with the new developments are trendy food spots like Hoppers and BAO. Hop a train from King’s Cross, and founders can be in Cambridge in 45 minutes to source talent or can be in Paris in two hours to strike a deal.
Who would have guessed that a little more than 20 years ago, this was one of the seediest areas in London?
“In the ’80s, crack and heroin made the area a major narcotics market,” Hussein Kanji, an investor at Hoxton Ventures, said, recalling syringes in tree trunks and gangs patrolling the streets. “In 1982, the local church was occupied by the English Collective of Prostitutes for 12 straight days.” Then, in the early 2000s, a real estate developer had a dream and, well, “now it is the AI hotbed of the United Kingdom,” Kanji said. “What a change.” Around 18 months ago, his portfolio company BioCorteX moved from the neighborhood Holborn to the Jellicoe building in King’s Cross, hoping to be near the action. “Lots going on in London right now,” Nik Sharma, co-founder of BioCorteX, told me. “Lots of hyperscalers moving in.” That includes, reportedly, Jeff Bezos’ AI company Prometheus, which is also said to be in talks to move into the Jellicoe.
There are around 3,600 AI startups in London, which, together, have raised around .1 billion out of the .8 billion raised in the city since late July, according to Dealroom. Since the start of June, AI-related startups have leased more than 1 million square feet of office space in London, according to the real estate firm Knight Frank. With that, prime rents in King’s Cross have risen 18% over the past three years, Chris Dunn, a commercial insight associate at the firm, told me. That percentage represents only the largest leases encompassing at least 10,000 square feet, like the ones OpenAI and Prometheus are signing. The shorter deals go for even more, he said, and now the vacancy rate for conventional office space is just 0.9%. “Demand has outstripped supply,” he continued.
Today, one of the big topics of the area is sovereignty. It was a wake-up call for many when Anthropic shut off access to Mythos and Fable this summer, leaving some in the ecosystem to conclude: “We’d better look after ourselves,” Saul Klein, co-founder of the VC firm Phoenix Court, told me.
Phoenix Court is located in the King’s Cross area and has three portfolio companies in the vicinity, including Olix (which just announced a .3 billion valuation), Early Health and CoMind. Robin Klein, co-founder of the firm, said the shutdown of Fable and Mythos access was a “small but sharp reminder that Europe can’t simply rent its AI capabilities and capacity; it needs to build and hold some of its own.” King’s Cross, he said, is where much of this building is actually happening.
“The bigger question,” he continued, “is whether the U.K. builds the infrastructure, compute, energy, capital, to make this self-reliance durable, rather than just hosting outposts of U.S. labs.”
Image Credits:Phoenix Court
Top founders want to stay
Simon Kohl, founder of Latent Labs, has offices in King’s Cross and San Francisco. The London office, at the moment, is growing faster, and he’s more bullish than ever on the ecosystem, he said. “The mood right now feels less like London trying to catch up and more like London becoming one of the default places to start a serious AI company,” he said. Look around and you are likely to see Wayve testing its autonomous cars. Founded in 2017 by co-founder Alex Kendall, the unicorn is one of London’s biggest success stories.
“Ten years ago, building a frontier AI company from London felt like an unusual choice,” Kendall told me. “Now it feels like an obvious one.” Wayve moved into King’s Cross in 2018 looking for a space that could double as a garage — “a rare combination in Central London,” Kendall said. He has watched the ecosystem mature around him — and it’s now evident that a startup can stay in London, raise serious capital, hire world-class AI talent, and remain globally competitive, he said. Down the street from Anthropic’s new 158,000-square-foot office is the AI agent builder Sierra and the AI video platform Synthesia.
Laura Gonzalez Florez, Synthesia’s chief of staff and head of people, says the company moved into its glossy new office building a year ago to accommodate its growing team. They were drawn to the area for the same reason as everyone else: “It’s very close to the airport … very close to where a lot of investors are,” she said.
Image Credits:Synthesia
Around two-thirds of Synthesia’s engineers are remote, Gonzalez Florez said, letting the company tap into an affordable, international, and diverse talent pool and helping it scale faster. “From London, we can hire and work, without any problem, people from anywhere, from Slovenia to Portugal,” she said.
Unsurprisingly, London’s AI boom is also causing a talent war.U.K. AI job postings have skyrocketed in the past few years, per data from PwC. When Anthropic announced it moved into town earlier this year, it listed, for example, a salary range of £260,000 to £630,000 for a machine learning research engineer when the average salary in London for the same role is around £102,000. Some founders in the U.K., like those in Silicon Valley, are being forced to raise more and bigger rounds to keep up.
“The real test is whether more globally significant AI companies are founded, funded, and scaled from the U.K., while continuing to attract the world’s best talent to build them here,” Zain Ali, founder of the King’s Cross-based AI legal firm Centuro, told me. “If that continues to happen, King’s Cross won’t just be an AI hub. It’ll become one of the U.K.’s most important strategic assets.”
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Thisformernotorious #redlight #districtis #nowone #worlds #top #hubs #TechCrunchUK](https://techcrunch.com/wp-content/uploads/2026/08/DM9A2852.jpg?w=680)

Post Comment