Following the illustrious line of calendar-spanning corporate events like Lobsterfest and Shark Week, Apple tried something new this year with a celebration unofficially known as Mac Week. (Fortunately for Apple, it just so happens to coincide with its earnings call on Thursday!) The company’s three-day product rollout for desktop hardware centered around the M4 chip, built for Apple Intelligence. We recount everything Apple spit out this week, including a new iMac, Mac mini, MacBook Pro and other goodies like Apple Intelligence’s official arrival on iOS, iPadOS and macOS.
iMac (M4)
The M4-powered iMac has the same design (apart from some new colors) but with more horsepower inside. Apple says the all-in-one desktop is 1.7 times faster for daily productivity and 2.1 times faster for more demanding tasks like gaming or photo editing. Like all new Macs announced this week, it loses the measly 8GB of RAM previously seen in the cheapest Macs, jumping to 16GB as the baseline. (Woo!)
The new iMac still has a 24-inch 4.5K Retina display encased in an aluminum unibody design. However, it adds a new nano-texture glass screen option for reduced glare and a 12MP Center Stage camera that supports Apple’s Desk View.
You can pre-order the M4 iMac now, starting at $1,299. Deliveries and in-store sales begin on November 8.
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Mac mini (M4, M4 Pro)
Apple’s little Mac that could lives up to its “mini” branding more than ever. The 2024 Mac mini is a mere five-inch by five-inch box, two inches tall. (That’s only slightly bigger than the Apple TV 4K!)
The new Mac mini is available in M4 and M4 Pro configurations. Apple says the M4 variant is up to 1.8 times faster than the M1 model from four years ago. Its graphics are up to 2.2 times faster. It should also be much better for Apple Intelligence: It supports 38 TOPS (tera operations per second) of AI processing power. That dwarfs the 18 TOPS from the (only one-year-old) M3 chip. It, too, starts with 16GB of RAM.
For the first time, the machine ditches legacy USB ports. It has two USB-C ports on the front and three Thunderbolt USB-C ports on the back (along with HDMI and Ethernet).
The M4 Mac mini is available to pre-order. It starts at $599, while the souped-up M4 Pro variant starts at $1,399. It arrives on November 9.
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MacBook Pro (M4, M4 Pro, M4 Max)
Most of Apple’s Mac sales are in the MacBook lineup, which makes sense. Not only can you use them on the go, but you can also grab a Thunderbolt cable and hook them up to the monitor of your choice to double as a desktop. So, the climax of Mac Week was the new M4-powered MacBook Pro.
The only new Mac with three chip tiers, the MacBook Pro comes in M4, M4 Pro and M4 Max options. Apple says the M4 Pro is up to three times faster than the M1 Pro, and the M4 Max is up to 3.5 times faster than the M1 Max. The M4 variant is up to 1.8 times faster than the M1-powered 13-inch MacBook Pro for photo editing. That jumps to 3.4 times faster for demanding work like rendering scenes in Blender.
Its Neural Engine for Apple Intelligence (and other AI) is over three times as powerful as the M1. Helping out on the AI front (and for all-around performance) is the same 16GB of RAM as a baseline.
The laptop offers the same nano-texture display option as the iMac and up to 1,000 nits of brightness for SDR content. It also adopts the 12MP Center Stage camera for much better built-in video call capabilities. The device has three Thunderbolt 4 ports and an estimated 24 hours of battery life — as Apple puts it, that’s the longest ever in a Mac.
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The new MacBook Pro is available in familiar 14-inch and 16-inch models. The smaller model with the M4 chip starts at $1,599, the M4 Pro variant starts at $1,999, and the ultra-high-end M4 Max will set you back at least $3,199. The 16-inch MacBook Pro starts at $2,499 with the M4 Pro chip, while an M4 Max flavor is $3,499 and up.
Apple Intelligence cometh
Apple’s first wave of on-device AI features is now in consumers’ hands, with no beta software required. This round includes writing tools like proofreading, rewiring and summaries, live call transcriptions and notification summaries.
The beginnings of a more intelligent Siri also arrived with this batch, including typed queries and an improved ability to recognize stutters or self-interruptions. You also get a neat new glowing border that announces to the world, “This ain’t the shitty Siri you’re used to!” But you’ll have to wait for the next wave of Siri upgrades for a more significant overhaul, like a better understanding of personal context.
Now, the bad news. Apple Intelligence is only available on a handful of recent devices in each of Apple’s major product categories. For the iPhone, that’s the iPhone 15 Pro / Pro Max and the new iPhone 16 lineup (including non-Pro models). You’ll need a model with an M-series chip on the iPad, although the new iPad mini (with an A17 Pro chip) is an exception. As for Macs, you’ll also need a model with M-series Apple silicon, which stretches back to the last four years of models.
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Apple Intelligence (round one) requires iOS 18.1, iPadOS 18.1 or macOS Sequoia 15.1. The X.2 variants of each OS will bring the next wave of AI features, like ChatGPT integration and Image Playground.
Announced at Apple’s September iPhone launch, the hearing features include a “clinically validated” hearing test, hearing protection (like for concerts) and the ability to use the device as a hearing aid if it detects mild to moderate impairment. (If severe, it will nudge you towards a professional.)
ChatGPT conversations can accumulate quickly if you regularly converse with the AI chatbot. Finding a particular bit of discussion with ChatGPT has been difficult, though, even with well-labeled thread names. OpenAI has released a new search feature for ChatGPT to address that issue. The feature lets you sift through past conversations by looking for specific terms, making it much easier to find bits you don’t totally remember or pull up old threads without having to dive deep into the list of threads.
The search tool is only available to those subscribing to ChatGPT Plus or Teams for now, though free users are supposed to be able to use it starting next month. To use the search tool, you just need to click on the magnifying glass icon at the top of the ChatGPT sidebar. Write in the word or phrase you want to find, and the AI chatbot will sort through your history to locate specific messages. If you have particularly long chat threads, that could save you a lot of time.
We’re starting to roll out the ability to search through your chat history on ChatGPT web.Now you can quickly & easily bring up a chat to reference, or pick up a chat where you left off. pic.twitter.com/YVAOUpFvzJOctober 29, 2024
ChatGPT search, not SearchGPT
Hearing the term search with the term ChatGPT immediately brings to mind SearchGPT, the rather imperfect web search feature teased by OpenAI this summer. The new tool is more like how you might hunt through a folder of documents or perhaps an email inbox.
And while OpenAI didn’t explicitly call it out, it would be logical for the search tool to learn from your interactions the way it does from your conversations. That might mean getting better at knowing the kind of conversation history you are likely to search for and maybe filtering the results.
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The search feature isn’t exactly earth-shattering, but it does at least bring ChatGPT to parity with some of its rivals like Google Gemini and Anthropic’s Claude. It fits with some of the other quality-of-life improvements to ChatGPT, including a better chat interface, autocomplete suggestions, and using “/” to immediately command ChatGPT to search online or generate images.
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Waymo has indicated it will use Google Gemini AI for its self-driving “robotaxis”. The company seems to be developing a new training model for its autonomous vehicles, which will draw data from Google’s Multimodal Large Language Model (MLLM) Gemini.
Waymo releases new research paper about MLLMs helping robotaxis
Waymo LLC was formerly known as the Google Self-Driving Car Project. It is an American autonomous driving technology company. Waymo has been gradually building hardware and software for robotaxis to safely ferry passengers on busy roads.
This new end-to-end training model would process sensor data and generate “future trajectories for autonomous vehicles.”. Needless to say, this would help Waymo’s driverless vehicles make smart decisions on the road. The Waymo robotaxis could confidently predict where to go and how to avoid obstacles.
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How will Google Gemini help Waymo?
For several years, algorithms for driverless vehicles have adopted compartmentalized solutions or modules to address each critical function. In other words, tech companies attempted to address aspects such as perception, mapping, prediction, and planning, independently of each other.
Such an approach has helped solve problems for autonomous vehicles. However, with this approach, companies have faced trouble while scaling their solutions. This is because of, “accumulated errors among modules and limited inter-module communication,” mentioned Waymo in the research paper.
Moreover, “pre-defined” parameters caused such solutions to falter in responding to “novel environments” as they struggled to “adapt”. Google’s Gemini is a Generative Artificial Intelligence (Gen AI). It is a “generalist” AI that the search giant has trained on vast sets of scraped data from the internet.
Secondly, Gen AI platforms have proven to demonstrate “superior” reasoning capabilities through techniques like “chain-of-thought reasoning,” suggested Waymo. Simply put, Gemini can mimic human reasoning, and hence, the LLM could “think” like a driver.
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Although Google Gemini could help Waymo, the EMMA AI would still need to play nice with new data, something that autonomous vehicles need to do constantly. Specifically speaking, EMMA has faced problems incorporating 3D sensor inputs from lidar or radar, admitted Waymo.
Last month at Meta Connect, Mark Zuckerberg said that Meta AI was “on track” to become the most-used generative AI assistant in the world. The company has now passed a significant milestone toward that goal, with Meta AI passing the 500 million user mark, Zuckerberg revealed during the company’s latest earnings call.
The half billion user mark comes just barely a year after the social network first launched its AI assistant last fall. Zuckerberg said the company still expects to become the “most-used” assistant by the end of 2024, though he’s never specified how the company is measuring that metric.
Meta’s assistant isn’t the only AI tool that’s boosting the company’s business. Zuckerberg said that AI improvements in its feed and video recommendations have led to an 8 percent increase in time spent on Facebook and a 5 percent increase for Instagram this year. Advertisers are also taking advantage of the company’s AI tools, he said, with more than 15 million ads created with generative AI in the last month alone. “We believe that there’s a lot more upside here,” Zuckerberg said.
Outside of AI, Meta’s Threads app also continues to surge. The service now has “almost 275 million” monthly users, according to Zuckerberg. “It’s been growing more than a million sign ups per day,” Zuckerberg said, adding that “engagement is growing too.”
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Over the last three days, 20 startups participated in the incredibly competitive Startup Battlefield at TechCrunch Disrupt. These 20 companies were selected as the best of the Startup Battlefield 200 and competed for a chance to take home the Startup Battlefield Cup and $100,000. After three days of intense pitching, we have a winner.
The startups taking part in the Startup Battlefield had all been hand-picked to participate in our startup competition. All the companies presented a live demo in front of multiple groups of VCs and tech leaders serving as judges for a chance to win $100,000 and the coveted Disrupt Cup.
After hours of deliberations, TechCrunch editors pored over the judges’ notes and narrowed the list down to five finalists: Gecko Materials, Luna, MabLab, Salva Health, and Stitch3D.
These startups made their way to the finale to demo in front of our final panel of judges, which included Navin Chaddha (Mayfield), Chris Farmer (SignalFire), Dayna Grayson (Construct Capital), Ann Miura-Ko (Floodgate), and Hans Tung (Notable Capital).
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We’re now ready to announce that the winner of TechCrunch Startup Battlefield 2024 is . . .
Winner: Salva Health
Six years ago, while researching for a college entrepreneurship competition, Valentina Agudelo identified a troubling gap in breast cancer survival rates between Latin America and the developed world, with women in her native Colombia and the rest of the continent dying at higher rates due to late detection. She realized that breast cancer is highly treatable when diagnosed early, yet many Latin American countries have large rural populations lacking access to mammograms and other diagnostic tools. So Agudelo and her two best friends decided to create Salva Health, a theoretical portable device that would detect breast cancer early.
It looks fake, or at least like a good illusion: There’s Gecko Materials founder Capella Kerst dangling a full wine bottle from her pinky finger, the only thing keeping it from smashing to pieces being the super-strong dry-adhesive her startup has brought to market. But it’s no trick. It’s the result of years of academic research that Kerst built on by inventing a method to mass-manufacture the adhesive. Inspired by the way real-life geckos’ feet grip surfaces, the adhesive is like a new Velcro — except it only needs one side, leaves no residue, and can detach as quickly as it attaches. It can do this at least 120,000 times and, as Kerst noted in a recent interview with TechCrunch, can stay attached for seconds, minutes, or even years.
These two companies follow in the footsteps of Startup Battlefield legends like Dropbox, Discord, Cloudflare and Mint on the Disrupt stage. With over 1,500 alumni having participated in the program, Startup Battlefield Alumni have collectively raised over $29 billion in funding with more than 200 successful exits.
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