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Artificial Intelligence

Apple says it’ll show its GenAI efforts ‘later this year’


Apple has tossed another crumb to investors wondering when the world will get to see some ‘Made in Cupertino’ GenAI: Expect Apple to reveal what it’s been working on in this buzzy slice of artificial intelligence “later this year”, per CEO Tim Cook.

During an earnings call yesterday, Apple’s chief exec emphasized its ongoing investment in AI, alongside other — as he put it — “groundbreaking innovation”, such as the technologies which underpin Apple’s Vision Pro VR/AR headset, saying: “We continue to spend a tremendous amount of time and effort and we’re excited to share the details of our ongoing work in that space later this year.”

There was no more steer on when exactly Cupertino will pull back the curtain on its AI efforts. But its annual developer confab, WWDC, typically takes place in June — and will certainly be one date to watch for any big reveals here.

Analysts tuned into the call were curious about “potential upcoming announcements on AI”, and during the Q&A section of the Q1 2024 results call, Cook tickled the fire of anticipation a little more, segueing from enthusing about “enterprise opportunities” for Vision Pro to referencing generative AI directly.

“In terms of generative AI, which I would guess is your focus, we have a lot of work going on internally, as I’ve alluded to before,” he said. “Our M.O., if you will, has always been to do work and then talk about work and not to get out in front of ourselves. And so we’re going to hold that to this as well. But we’ve got some things that we’re incredibly excited about, that we’ll be talking about later this year. ”

Apple’s senior leadership team was also asked about the level of investments it’s making in AI, given the scale of some of the bets being made by other tech firms.

Chief financial officer Luca Maestri responded briefly and bullishly — but without putting any figures on the level of spend — to that one. “We’ve always said we will never under invest in the business. So we are making all the investments that are necessary throughout our product development, software development services development,” he said. “So we will continue to invest in every area of the business — and at the appropriate level — and we’re very excited about what’s in store for us for the rest of the year.”

The iPhone maker also fielded a question about edge processing and AI during the call, with another analyst asking if it’s “a believer in the edge thesis that AI and processing on smartphones and devices like yours is going to have a huge role in AI and AI apps and that it’s something you guys can take advantage of”.

Cook wasn’t going to be drawn into tossing anything larger than crumbs (to continue the metaphor) — but he offered, perhaps, the equivalent of a wink toward the substance of the query, affirming: “Let me just say that I think there’s a huge opportunity for apple with Gen AI and and AI — without getting into more details and getting out in front of myself.”

Apple’s long-standing positioning of itself as pro-privacy and pro-user presents both a challenge and an opportunity when it comes to generative AI which demands vast amounts of (often personal) data to train AI models in the sought for drive for utility.

However if Apple can offer users GenAI tools that don’t demand users’ data is uploaded to a third party cloud somewhere, with all the privacy and security risks that can entail, and instead processing to power the tech can be done locally, on device, it could — potentially — carve itself (and its ecosystem) a differentiating niche vs the current data-gobbling market leaders in GenAI. (OpenAI, for instance, is now facing a charge its AI chatbot, ChatGPT, breaches Europe’s data protection laws in areas such as AI model training.)

When it comes to edge AI, performance will of course be key. But this is Apple — and finessing products, via its own hardware and software development, is its business — so if anyone has both the rational and resources to pull off development of privacy-conscious GenAI it’s going to be Apple.



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by Team SNFYI

Facebook is testing a new feature that invites some users—mainly in the US and Canada—to let Meta AI access parts of their phone’s camera roll. This opt-in “cloud processing” option uploads recent photos and videos to Meta’s servers so the AI can offer personalized suggestions, such as creating collages, highlight reels, or themed memories like birthdays and graduations. It can also generate AI-based edits or restyles of those images. Meta says this is optional and assures users that the uploaded media won’t be used for advertising. However, to enable this, people must agree to let Meta analyze faces, objects, and metadata like time and location. Currently, the company claims these photos won’t be used to train its AI models—but they haven’t completely ruled that out for the future. Typically, only the last 30 days of photos get uploaded, though special or older images might stay on Meta’s servers longer for specific features. Users have the option to disable the feature anytime, which prompts Meta to delete the stored media after 30 days. Privacy experts are concerned that this expands Meta’s reach into private, unpublished images and could eventually feed future AI training. Unlike Google Photos, which explicitly states that user photos won’t train its AI, Meta hasn’t made that commitment yet. For now, this is still a test run for a limited group of people, but it highlights the tension between AI-powered personalization and the need to protect personal data.

by Team SNFYI

News Update Bymridul     |    March 14, 2024 Meesho, an online shopping platform based in Bengaluru, has announced its largest Employee Stock Ownership Plan (ESOP) buyback pool to date, totaling Rs 200 crore. This buyback initiative extends to both current and former employees, providing wealth creation opportunities for approximately 1,700 individuals. Ashish Kumar Singh, Meesho’s Chief Human Resources Officer, emphasized the company’s commitment to rewarding its teams, stating, “At Meesho, our employees are the driving force behind our success.” Singh further highlighted the company’s dedication to providing opportunities for wealth creation despite prevailing macroeconomic conditions. This marks the fourth wealth generation opportunity at Meesho, with the size of the buyback program increasing each year. In previous years, Meesho conducted buybacks worth over Rs 8.2 crore in February 2020, Rs 41.4 crore in November 2020, and Rs 45.5 crore in October 2021. Meesho’s profitability journey began in July 2023, making it the first horizontal Indian e-commerce company to achieve profitability. Despite turning profitable, Meesho continues to maintain positive cash flow and focuses on enhancing efficiencies across various cost items. The company’s revenue from operations for FY 2022-23 witnessed a remarkable growth of 77% over the previous year, amounting to Rs 5,735 crore. This growth can be attributed to Meesho’s leadership position as the most downloaded shopping app in India in both 2022 and 2023, increased transaction frequency among existing customers, and a diversified category mix. Additionally, Meesho’s focus on improving monetization through value-added seller services contributed to its revenue growth. Meesho also disclosed its audited performance for the first half of FY 2023-24, reporting consolidated revenues from operations of Rs 3,521 crore, marking a 37% year-over-year increase. The company achieved profitability in Q2 FY24, with a significant reduction in losses compared to the previous year. Furthermore, Meesho recorded impressive app download numbers, reaching 145 million downloads in India in 2023 and surpassing 500 million downloads in H1 FY 2023-24. Follow Startup Story Source link

by Team SNFYI

You might’ve heard of Grok, X’s answer to OpenAI’s ChatGPT. It’s a chatbot, and, in that sense, behaves as as you’d expect — answering questions about current events, pop culture and so on. But unlike other chatbots, Grok has “a bit of wit,” as X owner Elon Musk puts it, and “a rebellious streak.” Long story short, Grok is willing to speak to topics that are usually off limits to other chatbots, like polarizing political theories and conspiracies. And it’ll use less-than-polite language while doing so — for example, responding to the question “When is it appropriate to listen to Christmas music?” with “Whenever the hell you want.” But Grok’s ostensible biggest selling point is its ability to access real-time X data — an ability no other chatbots have, thanks to X’s decision to gatekeep that data. Ask it “What’s happening in AI today?” and Grok will piece together a response from very recent headlines, while ChatGPT, by contrast, will provide only vague answers that reflect the limits of its training data (and filters on its web access). Earlier this week, Musk pledged that he would open source Grok, without revealing precisely what that meant. So, you’re probably wondering: How does Grok work? What can it do? And how can I access it? You’ve come to the right place. We’ve put together this handy guide to help explain all things Grok. We’ll keep it up to date as Grok changes and evolves. How does Grok work? Grok is the invention of xAI, Elon Musk’s AI startup — a startup reportedly in the process of raising billions in venture capital. (Developing AI’s expensive.) Underpinning Grok is a generative AI model called Grok-1, developed over the course of months on a cluster of “tens of thousands” of GPUs (according to an xAI blog post). To train it, xAI sourced data both from the web (dated up to Q3 2023) and feedback from human assistants that xAI refers to as “AI tutors.” On popular benchmarks, Grok-1 is about as capable as Meta’s open source Llama 2 chatbot model and surpasses OpenAI’s GPT-3.5, xAI claims. Image Credits: xAI Human-guided feedback, or reinforcement learning from human feedback (RLHF), is the way most AI-powered chatbots are fine-tuned these days. RLHF involves training a generative model, then gathering additional information to train a “reward” model and fine-tuning the generative model with the reward model via reinforcement learning. RLHF is quite good at “teaching” models to follow instructions — but not perfect. Like other models, Grok is prone to hallucinating, sometimes offering misinformation and false timelines when asked about news. And these can be severe — like wrongly claiming that the Israel–Palestine conflict reached a ceasefire when it hadn’t. For questions that stretch beyond its knowledge base, Grok leverages “real-time access” to info on X (and from Tesla, according to Bloomberg). And, similar to ChatGPT, the model has internet browsing capabilities, enabling it to search the web for up-to-date information about topics. Musk has promised improvements with the …