Technology

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

Published

4 months ago

July 30, 2024

IAM

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

Technology

Flipkart co-founder Binny Bansal is leaving PhonePe’s board

Published

7 mins ago

November 22, 2024

IAM

Flipkart co-founder Binny Bansal has stepped down three-quarters from PhonePe’s board after making an identical move on the e-commerce giant.

Bengaluru-based PhonePe said it has appointed Manish Sabharwal, executive director at recruitment and human resources firm Teamlease, as an independent director and chairman of the audit committee.

Bansal played a key role in Flipkart’s acquisition of PhonePe in 2016 and has since served on the fintech’s board. The Walmart-backed startup, which operates India’s hottest mobile payment app, spun off from Flipkart in 2022 and was valued at $12 billion in funding rounds that raised about $850 million last 12 months.

Bansal still holds about 1% of PhonePe. Neither party explained why they were leaving the board.

“I would like to express my heartfelt gratitude to Binny Bansal for being one of the first and staunchest supporters of PhonePe,” Sameer Nigam, co-founder and CEO of PhonePe, said in a press release. His lively involvement, strategic advice and private mentoring have profoundly enriched our discussions. We will miss Binny!”

This article was originally published on : techcrunch.com

Technology

The company is currently developing washing machines for humans

Published

7 hours ago

November 22, 2024

IAM

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

Technology

Zepto raises another $350 million amid retail upheaval in India

Published

14 hours ago

November 21, 2024

IAM

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