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Apple says it took a ‘responsible’ approach to training its Apple Intelligence models

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Apple published technical paper detailing the models developed for Apple Intelligence, a range of generative AI features coming to iOS, macOS, and iPadOS over the subsequent few months.

In the article, Apple opposes accusations that it took an ethically questionable approach to training a few of its models, reiterating that it didn’t use private user data but as a substitute relied on a combination of knowledge publicly available and licensed to Apple Intelligence.

“(The) pre-training dataset consists of… data we have licensed from publishers, curated publicly available or open datasets, and publicly available information crawled by our web crawler, Applebot,” Apple writes within the article. “Given our focus on protecting user privacy, we note that no private Apple user data is included in the data mix.”

Proof News in July reported that Apple used a dataset called The Pile, which comprises captions from a whole lot of 1000’s of YouTube videos, to train a family of models designed for on-device processing. Many YouTube creators whose captions were wolfed up by The Pile were unaware of this and didn’t consent to it; Apple later issued a statement saying it had no intention of using the models to power any AI features in its products.

A technical paper that offers a sneak peek on the models that Apple first unveiled at WWDC 2024 in June, titled Apple Foundation Models (AFM), emphasizes that the training data for the AFM models was acquired in a “responsible” manner — or at the least responsibly by Apple’s definition.

The training data for the AFM models includes publicly available Internet data, in addition to licensed data from undisclosed publishers. According to The New York Times, Apple I contacted several publishers in late 2023, including NBC, Condé Nast, and IAC, with multi-year deals price at the least $50 million to train models on publishers’ news archives. Apple’s AFM models were also trained on open-source code hosted on GitHub, specifically Swift, Python, C, Objective-C, C++, JavaScript, Java, and Go code.

Training models on code without permission, even open source, is a point of contention amongst developers. Some developers have argued that some open-source code bases are unlicensed or don’t allow AI training of their terms of use. However, Apple says it has “licensed” the code to try to include only repositories with minimal usage restrictions, reminiscent of those licensed under the MIT, ISC, or Apache licenses.

To boost the mathematical skills of the AFM models, Apple specifically included math questions and answers from web sites, math forums, blogs, tutorials, and seminars within the training set, according to the article. The company also used “high-quality, publicly available” data sets (which the article doesn’t specify) with “licenses that allow use to train… models,” filtered to remove sensitive information.

In total, the training dataset for the AFM models weighs in at about 6.3 trillion tokens. (Tokens are small pieces of knowledge which are typically easier for generative AI models to digest.) By comparison, that’s lower than half the variety of tokens — 15 trillion — that Meta used to train its flagship text-generating model, Llama 3.1 405B.

Apple acquired additional data, including human and artificial data, to refine the AFM models and attempt to mitigate any undesirable behaviors reminiscent of toxicity release.

“Our models are designed to help users perform on a regular basis tasks on Apple products in a way that’s well-established
in Apple’s core values ​​and rooted in our principles of responsible AI at every stage,” the corporate said.

There is not any hard evidence or shocking insights within the article, and that is due to its careful design. Rarely are such articles very revealing, due to pressures of competition, but in addition because revealing much of the data could get corporations into legal trouble.

Some corporations that train models by scraping public web data claim that their practice is protected by fair use doctrine. But that is a difficulty that is extremely controversial and the topic of a growing variety of lawsuits.

Apple notes within the article that it allows webmasters to block the crawler from scraping their data. But that puts individual creators in a difficult position. What’s an artist to do if, for instance, their portfolio is hosted on a site that refuses to block Apple from scraping their data?

Court battles will resolve the fate of generative AI models and the way they’re trained. For now, though, Apple is trying to position itself as an ethical player while avoiding unwanted legal scrutiny.

This article was originally published on : techcrunch.com
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The company is currently developing washing machines for humans

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Forget about cold baths. Washing machines for people may soon be a brand new solution.

According to at least one Japanese the oldest newspapersOsaka-based shower head maker Science has developed a cockpit-shaped device that fills with water when a bather sits on a seat in the center and measures an individual’s heart rate and other biological data using sensors to make sure the temperature is good. “It also projects images onto the inside of the transparent cover to make the person feel refreshed,” the power says.

The device, dubbed “Mirai Ningen Sentakuki” (the human washing machine of the longer term), may never go on sale. Indeed, for now the company’s plans are limited to the Osaka trade fair in April, where as much as eight people will have the option to experience a 15-minute “wash and dry” every day after first booking.

Apparently a version for home use is within the works.

This article was originally published on : techcrunch.com
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Zepto raises another $350 million amid retail upheaval in India

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Zepto, snagging $1 billion in 90 days, projects 150% annual growth

Zepto has secured $350 million in latest financing, its third round of financing in six months, because the Indian high-speed trading startup strengthens its position against competitors ahead of a planned public offering next yr.

Indian family offices, high-net-worth individuals and asset manager Motilal Oswal invested in the round, maintaining Zepto’s $5 billion valuation. Motilal co-founder Raamdeo Agrawal, family offices Mankind Pharma, RP-Sanjiv Goenka, Cello, Haldiram’s, Sekhsaria and Kalyan, in addition to stars Amitabh Bachchan and Sachin Tendulkar are amongst those backing the brand new enterprise, which is India’s largest fully national primary round.

The funding push comes as Zepto rushes so as to add Indian investors to its capitalization table, with foreign ownership now exceeding two-thirds. TechCrunch first reported on the brand new round’s deliberations last month. The Mumbai-based startup has raised over $1.35 billion since June.

Fast commerce sales – delivering groceries and other items to customers’ doors in 10 minutes – will exceed $6 billion this yr in India. Morgan Stanley predicts that this market shall be value $42 billion by 2030, accounting for 18.4% of total e-commerce and a pair of.5% of retail sales. These strong growth prospects have forced established players including Flipkart, Myntra and Nykaa to cut back delivery times as they lose touch with specialized delivery apps.

While high-speed commerce has not taken off in many of the world, the model seems to work particularly well in India, where unorganized retail stores are ever-present.

High-speed trading platforms are creating “parallel trading for consumers seeking convenience” in India, Morgan Stanley wrote in a note this month.

Zepto and its rivals – Zomato-owned Blinkit, Swiggy-owned Instamart and Tata-owned BigBasket – currently operate on lower margins than traditional retail, and Morgan Stanley expects market leaders to realize contribution margins of 7-8% and adjusted EBITDA margins to greater than 5% by 2030. (Zepto currently spends about 35 million dollars monthly).

An investor presentation reviewed by TechCrunch shows that Zepto, which handles greater than 7 million total orders every day in greater than 17 cities, is heading in the right direction to realize annual sales of $2 billion. It anticipates 150% growth over the following 12 months, CEO Aadit Palicha told investors in August. The startup plans to go public in India next yr.

However, the rapid growth of high-speed trading has had a devastating impact on the mom-and-pop stores that dot hundreds of Indian cities, towns and villages.

According to the All India Federation of Consumer Products Distributors, about 200,000 local stores closed last yr, with 90,000 in major cities where high-speed trading is more prevalent.

The federation has warned that without regulatory intervention, more local shops shall be vulnerable to closure as fast trading platforms prioritize growth over sustainable practices.

Zepto said it has created job opportunities for tons of of hundreds of gig employees. “From day one, our vision has been to play a small role in nation building, create millions of jobs and offer better services to Indian consumers,” Palicha said in an announcement.

Regulatory challenges arise. Unless an e-commerce company is a majority shareholder of an Indian company or person, current regulations prevent it from operating on a listing model. Fast trading corporations don’t currently follow these rules.

This article was originally published on : techcrunch.com
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Wiz acquires Dazz for $450 million to expand cybersecurity platform

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Wizardone of the talked about names within the cybersecurity world, is making a major acquisition to expand its reach of cloud security products, especially amongst developers. This is buying Dazzlespecialist in solving security problems and risk management. Sources say the deal is valued at $450 million, which incorporates money and stock.

This is a leap within the startup’s latest round of funding. In July, we reported that Dazz had raised $50 million at a post-money valuation of just below $400 million.

Remediation and posture management – two areas of focus for Dazz – are key services within the cybersecurity market that Wiz hasn’t sorted in addition to it wanted.

“Dazz is a leader in this market, with the best talent and the best customers, which fits perfectly into the company culture,” Assaf Rappaport, CEO of Wiz, said in an interview.

Remediation, which refers to helping you understand and resolve vulnerabilities, shapes how an enterprise actually handles the various vulnerability alerts it could receive from the network. Posture management is a more preventive product: it allows a company to higher understand the scale, shape and performance of its network from a perspective, allowing it to construct higher security services around it.

Dazz will proceed to operate as a separate entity while it’s integrated into the larger Wiz stack. Wiz has made a reputation for itself as a “one-stop shop,” and Rappaport said the integrated offering will proceed to be a core a part of it.

He believes this contrasts with what number of other SaaS corporations are built. In the safety industry, there are, Rappaport said, “a lot of Frankenstein mashups where companies prioritize revenue over building a single technology stack that actually works as a platform.” It could be assumed that integration is much more necessary in cybersecurity than in other areas of enterprise IT.

Wiz and Dazz already had an in depth relationship before this deal. Merat Bahat — the CEO who co-founded Dazz with Tomer Schwartz and Yuval Ofir (CTO and VP of R&D, respectively) — worked closely with Assaf Rappaport at Microsoft, which acquired his previous startup Adallom.

After Rappaport left to found Wiz together with his former Adallom co-founders, CTO Ami Luttwak, VP of Product Yinon Costica and VP of R&D Roy Reznik, Bahat was one in all the primary investors. Similarly, when Bahat founded Dazz, Assaf was a small investor in it.

The connection goes deeper than work colleagues. Bahat and Rappaport are also close friends, and she or he was the second family of Mickey, Rappaport’s beloved dog, referred to as Chief Dog Officer Wiz (together with LinkedIn profile). Once the deal was done, the 2 faced two very sad events: each Bahat and Mika’s mother died.

“We hope for a new chapter of positivity,” Bahat said. The cycle of life does indeed proceed.

Rumors of this takeover began to appear earlier this month; Rappaport confirmed that they then began talking seriously.

But that is not the one M&A conversation Wiz has gotten involved in. Earlier this 12 months, Google tried to buy Wiz itself for $23 billion to construct a major cybersecurity business. Wiz walked away from the deal, which might have been the biggest in Google’s history, partly because Rappaport believed Wiz could turn into a fair larger company by itself terms. And that is what this agreement goals to do.

This acquisition is a test for Wiz, which earlier this 12 months filled its coffers with $1 billion solely for M&A purposes (it has raised almost $2 billion in total, and we hear the subsequent round will close in just a few weeks). . Other offers included purchasing Gem security for $350 million, but Dazz is its largest acquisition ever.

More mergers and acquisitions could also be coming. “We believe next year will be an acquisition year for us,” Rappaport said.

In an interview with TC, Luttwak said that one in all Wiz’s priorities now’s to create more tools for developers that have in mind what they need to do their jobs.

Enterprises have made significant investments in cloud services to speed up operations and make their IT more agile, but this shift has include a significantly modified security profile for these organizations: network and data architectures are more complex and attack surfaces are larger, creating opportunities for malicious hackers to find ways to to hack into these systems. Artificial intelligence makes all of this far more difficult when it comes to malicious attackers. (It’s also a chance: the brand new generation of tools for our defense relies on artificial intelligence.)

Wiz’s unique selling point is its all-in-one approach. Drawing data from AWS, Azure, Google Cloud and other cloud environments, Wiz scans applications, data and network processes for security risk aspects and provides its users with a series of detailed views to understand where these threats occur, offering over a dozen products covering the areas, corresponding to code security, container environment security, and provide chain security, in addition to quite a few partner integrations for those working with other vendors (or to enable features that Wiz doesn’t offer directly).

Indeed, Wiz offered some extent of repair to help prioritize and fix problems, but as Luttwak said, the Dazz product is solely higher.

“We now have a platform that actually provides a 360-degree view of risk across infrastructure and applications,” he said. “Dazz is a leader in attack surface management, the ability to collect vulnerability signals from the application layer across the entire stack and build the most incredible context that allows you to trace the situation back to engineers to help with remediation.”

For Dazz’s part, once I interviewed Bahat in July 2024, when Dazz raised $50 million at a $350 million valuation, she extolled the virtues of constructing strong solutions and this week said the third quarter was “amazing.”

“But market dynamics are what trigger these types of transactions,” she said. She confirmed that Dazz had also received takeover offers from other corporations. “If you think about the customers and joint customers that we have with Wiz, it makes sense for them to have it on one platform.”

And a few of Dazz’s competitors are still going it alone: ​​Cyera, like Dazz, an authority in attack surface management, just yesterday announced a rise of $300 million at a valuation of $5 billion (which confirms our information). But what’s going to he do with this money? Make acquisitions, after all.

Wiz says it currently has annual recurring revenue of $500 million (it has a goal of $1 billion ARR next 12 months) and has greater than 45% of its Fortune 100 customers. Dazz said ARR is within the tens of hundreds of thousands of dollars and currently growing 500% on a customer base of roughly 100 organizations.

This article was originally published on : techcrunch.com
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