Five years is an awful lot of time in the tech industry. Darling startups find ways to crash and burn. Trends that seem unstoppable sputter-out. In the field of artificial intelligence, the past five years have been nothing short of transformative.
Facebook’s AI Research lab (FAIR) turns five years old this month, and just as the social media giant has left an indelible mark on the broader culture — for better or worse — the work coming out of FAIR has seen some major impact in the AI research community and entrenched itself in the way Facebook operates.
“You wouldn’t be able to run Facebook without deep learning,” Facebook Chief AI Scientist Yann LeCun tells TechCrunch. “It’s very, very deep in every aspect of the operation.”
Reflecting on the formation of his team, LeCun recalls his central task in initially creating the research group was “inventing what it meant to do research at Facebook.”
“Facebook didn’t have any research lab before FAIR, it was the first one, until then the company was very much focused on short-term engineering projects with six-month deadlines, if not less,” he says.
Five years after its formation, FAIR’s influence permeates the company. The group has labs in Menlo Park, New York, Paris, Montreal, Tel Aviv, Seattle, Pittsburgh and London. They’ve partnered with academic institutions and published countless papers and studies, many of which the group has enumerated in this handy five-year anniversary timeline here.
“I said ‘No’ to creating a research lab for my first five years at Facebook,” CTO Mike Schroepfer wrote in a Facebook post. “In 2013, it became clear AI would be critical to the long-term future of Facebook. So we had to figure this out.”
The research group’s genesis came shortly after LeCun stopped by Mark Zuckerberg’s house for dinner. “I told [Zuckerberg] how research labs should be organized, particularly the idea of practicing open research.” LeCun said. “What I heard from him, I liked a lot, because he said openness is really in the DNA of the company.”
FAIR has the benefit of longer timelines that allow it to be more focused in maintaining its ethos. There is no “War Room” in the AI labs, and much of the group’s most substantial research ends up as published work that benefits the broader AI community. Nevertheless, in many ways, AI is very much an arms race for Silicon Valley tech companies. The separation between FAIR and Facebook’s Applied Machine Learning (AML) team, which focuses more on imminent product needs, gives the group a “huge, huge amount of leeway to really think about the long term,” LeCun says.
I chatted with LeCun about some of these long-term visions for the company, which evolved into him spitballing about what he’s working on now and where he’d like to see improvements. “First, there’s going to be considerable progress in things that we already have quite a good handle on…”
A big trend for LeCun seems to be FAIR doubling down on work that impacts how people can more seamlessly interact with data systems and get meaningful feedback.
“We’ve had this project that is a question-and-answer system that basically can answer any question if the information is somewhere in Wikipedia. It’s not yet able to answer really complicated questions that require extracting information from multiple Wikipedia articles and cross-referencing them,” LeCun says. “There’s probably some progress there that will make the next generation of virtual assistants and data systems considerably less frustrating to talk to.”
Some of the biggest strides in machine learning over the past five years have taken place in the vision space, where machines are able to parse out what’s happening in an image frame. LeCun predicts greater contextual understanding is on its way.
“You’re going to see systems that can not just recognize the main object in an image but basically will outline every object and give you a textual description of what’s happening in the image, kind of a different, more abstract understanding of what’s happening.”
FAIR has found itself tackling disparate and fundamental problems that have wide impact on how the rest of the company functions, but a lot of these points of progress sit deeper in the five-year timeline.
FAIR has already made some progress in unsupervised learning, and the company has published work on how they are utilizing some of these techniques to translate between languages for which they lack sufficient training data so that, in practical terms, users needing translations from something like Icelandic to Swahili aren’t left out in the cold.
As FAIR looks to its next five years, LeCun contends there are some much bigger challenges looming on the horizon that the AI community is just beginning to grapple with.
“Those are all relatively predictable improvements,” he says. “The big prize we are really after is this idea of self-supervised learning — getting machines to learn more like humans and animals and requiring that they have some sort of common sense.”
A Capable, Complicated Answer To Going Electric
Regular Sorento ownership starts at $30,090 (plus $1,325 destination), with Kia’s 2.5-liter four-cylinder gas engine. Step up to the Sorento Hybrid, however, and Kia adds electrification and takes away engine capacity. Priced from $36,690 (plus destination), there’s a 1.6-liter turbocharged four-cylinder gas engine that — with the assistance of an electric motor — nudges up power while also improving fuel economy.
In fact, you get 227 horsepower and 258 lb-ft of torque, reasonable if not excessive, compared to the non-hybrid’s 191 horsepower and 182 lb-ft of torque. Rather than the continuously variable transmission we’re used to seeing in mild hybrids, Kia instead relies on a six-speed automatic. The non-hybrid Sorento gets two more gears in its auto.
With both engines, front-wheel drive is standard on the lower trims and all-wheel drive is an option. Kia’s system has a center-locking differential, too, though it’s hard to imagine Sorento owners venturing too far off-road with their SUVs. It’s a $2,300 upgrade on the Sorento Hybrid EX and standard on the Sorento Hybrid SX Prestige (from $42,490 plus destination).
Google Pixel 8 Pro Gets A Serious Upgrade: Here’s What’s New
The front camera doesn’t change from the previous model, and clicks selfies at 10.5MP with a 95-degrees-wide field of view. Unlike the rear cameras, aperture values also remain the same on the front camera. But even with the same underlying hardware, the Pixel 8 Pro can now click sharper selfies thanks to the valuable addition of autofocus.
Speaking of other improvements, the Pixel 8 Pro gets better video recording capabilities with improved HDR+ recording, powered by what Google calls “Video Boost.” The Pixel 8 Pro is also the first to extend Night Sight to videos. In addition, the Tensor G3 chip has been reported to bring support for AV1 encoding at resolutions up to 4K at 60fps.
That means the Pixel 8 Pro will be more efficient at compressing raw video footage to web-compliant formats without much loss in quality. Further, the Audio Magic Eraser will eliminate distracting background noise and unwanted sounds from the audio.
Besides video, the Pixel 8 Pro also gets a horde of software features for photography. First, as previewed at Google I/O 2023, Magic Eraser is expanding new AI-based editing features that can create and fill portions of an image, and this tool is now called “Magic Editor.” Secondly, “Best Take” will help you fix or replace any unpleasant parts of a photo, ensuring you always have the best possible pictures.
These Are The Cheapest Places In America To Buy A Car
Before we list the cheapest cities across the U.S. to buy used cars, it is important to know that the national average price for a used car stands at $34,227. However, if you happen to shop in Cleveland-Akron (Canton), the average price of used cars sold in the area is $2,769 lower than the national average, with the typical used car costing just $31,458.
Buyers in Cincinnati, Ohio, come in at a close second with an average used car priced at $31,622. There isn’t much difference between the rest of the cities in the top 10, with Norfolk-Portsmouth-Newport News, Va., coming in at as the third least expensive city with an average used car costing $31,901 there.
The rest of the list includes cities like Fresno-Visalia, Calif. ($31,912), Orlando-Daytona Beach, Fla. ($31,971), Detroit, Mich. ($31,990), Columbus, Ohio ($32,177), Pittsburgh, Pa. ($32,286), Indianapolis, Ind. ($32,418), and Oklahoma City, Okla., ($32,443).
There are a few reasons why these cities are cheaper places to buy a used car. One is that the cost of living in these cities is generally lower than in other parts of the country. Another reason is that these cities have a lot of competition among used car dealerships. This competition drives down prices and gives buyers more bargaining power. Finally, these cities are all located in the Midwest and Northeast, which are two regions of the country that are known for having more used cars on the market. Having a larger selection of used cars to choose from means you are more likely to find a good deal.
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