... includes all of the major AI methods for (a) representing knowledge about a task or a problem area, and (b) reasoning about a problem.
The evolution and convergence of technology has fueled a vibrant marketplace for timely and accurate geospatial data. Every day billions of handheld and IoT devices along with thousands of airborne and satellite remote sensing platforms generate hundreds of exabytes of location-aware data. This boom of geospatial big data combined with advancements in machine learning is enabling organizations across industry to build new products and capabilities. Maps leveraging geospatial data are used widely across industry, spanning multiple use cases, including disaster recovery, defense and intel, infrastructure and health services. For example, numerous companies provide localized drone-based services such as mapping and site inspection (reference Developing for the Intelligent Cloud and Intelligent Edge).
Facebook has scored an impressive feat involving AI that can navigate without any map. Facebook's wish for bragging rights, although they said they have a way to go, were evident in its blog post, "Near-perfect point-goal navigation from 2.5 billion frames of experience." Long story short, Facebook has delivered an algorithm that, quoting MIT Technology Review, lets robots find the shortest route in unfamiliar environments, opening the door to robots that can work inside homes and offices." And, in line with the plain-and-simple, Ubergizmo's Tyler Lee also remarked: "Facebook believes that with this new algorithm, it will be capable of creating robots that can navigate an area without the need for maps...in theory, you could place a robot in a room or an area without a map and it should be able to find its way to its destination." Erik Wijmans and Abhishek Kadian in the Facebook Jan. 21 post said that, well, after all, one of the technology key challenges is "teaching these systems to navigate through complex, unfamiliar real-world environments to reach a specified destination--without a preprovided map." Facebook has taken on the challenge. The two announced that Facebook AI created a large-scale distributed reinforcement learning algorithm called DD-PPO, "which has effectively solved the task of point-goal navigation using only an RGB-D camera, GPS, and compass data," they wrote. DD-PPO stands for decentralized distributed proximal policy optimization. This is what Facebook is using to train agents and results seen in virtual environments such as houses and office buildings were encouraging. The bloggers pointed out that "even failing 1 out of 100 times is not acceptable in the physical world, where a robot agent might damage itself or its surroundings by making an error." Beyond DD-PPO, the authors gave credit to Facebook AI's open source AI Habitat platform for its "state-of-the-art speed and fidelity." AI Habitat made its open source announcement last year as a simulation platform to train embodied agents such as virtual robots in photo-realistic 3-D environments. Facebook said it was part of "Facebook AI's ongoing effort to create systems that are less reliant on large annotated data sets used for supervised training." InfoQ had said in July that "The technology was taking a different approach than relying upon static data sets which other researchers have traditionally used and that Facebook decided to open-source this technology to move this subfield forward." Jon Fingas in Engadget looked at how the team worked toward AI navigation (and this is where that 25 billion number comes in). "Previous projects tend to struggle without massive computational power.
This project may be Apple's fallback to building its own car. From 2014 to 2019, roughly, Apple's Project Titan was a ground-up autonomous, electrified vehicle project. Apple found out that building a car is enormously complex, there are regulatory hurdles to clear far tougher than for phones or PCs, and you can't build a world-class auto factory in a couple of years. Apple also found out that not everyone wants to run a contract factory for Apple, including BMW and Daimler, and if there was an agreement, divorce court would have followed closely. Too many egos and everyone would want the final say.
Google is silently churning out many new technologies with wide ranging and far reaching impacts. The AI platform that Google is working on for quite some time has already been integrated with its digital assistant called Google Assistant that has been successfully leveraged into smart speakers of all types including the Google's own Google Home. But, this was just the beginning and company is on the verge of delivering something new this time. Google made tremendous research in the fields like natural language processing and synthesis. Google for quite some time is working on a new technology that can allow people more ease without relying too much on the Assistant.
Training an artificial intelligence agent to do something like navigate a complex 3D world is computationally expensive and time-consuming. In order to better create these potentially useful systems, Facebook engineers derived huge efficiency benefits from, essentially, leaving the slowest of the pack behind. It's part of the company's new focus on "embodied AI," meaning machine learning systems that interact intelligently with their surroundings. That could mean lots of things -- responding to a voice command using conversational context, for instance, but also more subtle things like a robot knowing it has entered the wrong room of a house. Exactly why Facebook is so interested in that I'll leave to your own speculation, but the fact is they've recruited and funded serious researchers to look into this and related domains of AI work.
We're constantly being bombarded with new and exciting technological developments – but few are as intriguing as the rise of artificial intelligence. Once the stuff of sci-fi stories, artificially intelligent devices are in homes around the world now, and this technology is a powerful force which needs forward-thinking professionals behind it. But what does human science have to do with any of this? We've teamed up with IE University and their School of Human Sciences and Technology to find out. Artificial intelligence and machines will most likely never be able to replicate emotional intelligence and human creativity.
Already, about one in four U.S. consumers has a home personal assistant at their beck and call, thanks to the success of smart speakers like Amazon Echo and Google Nest. But many users are just scratching the surface of what these gadgets can do. If you aren't familiar with the speakers (both starting at $35), you wake up your artificial intelligence-driven helper with a keyword – "Alexa" for Amazon devices and "OK, Google" for a Google Nest or Google Home speaker – followed by a question or command. A human-like voice will give you a response, whether you want to hear the weather, a specific song, set a timer for the oven, or control your smart devices in your home, such as adjusting lighting or a thermostat. One-fourth of U.S. consumers (25%) will use a smart speaker in 2020, up from 17% in 2018, according to research firm eMarketer.
Python is a very popular multi-paradigm programming language. Object-oriented programming and structured programming are fully supported in this, and many of its features support functional programming and aspect-oriented programming – for that matter. This easy-to-understand course aims to teach everyone the basics of Python Language, learning outcomes, benefits of learning Python, advantages of Python etc. You will learn where to use Python Language and know about who would actually use it in their daily office lives. You will also learn the comparative parameters of python with other programming languages, in the world – with a highlight on popularity and frameworks of Python.
Technical singularity is defined as a hypothetical future of superhuman machines with a cognitive capability far beyond the capacity of human minds. In the journey toward this potential technology revolution is something that I have been focused on called artificial swarm intelligence. A starling murmuration, something that people have told me is awe-inspiring, is a marvel of nature similar to an army of ants or a swarm of bees. How do all these individual entities organize around a common mission that includes a form of collaboration and unified orchestration as a team? When thinking about swarms of AI bots or even nanobots, the foundational concept we want to define is what exactly AI bot are.
Tinder is to'swipe left' on catfishing as the popular dating app starts using artificial intelligence to check that profile photos uploaded by users are genuine. The photo verification feature will allow members to get their images authenticated by posing for a series of real-time selfies. Human-assisted artificial intelligence technology will then compare these submission to existing profile photos to confirm that they do match up. Once a person's photos have been verified, their profile will be granted a blue checkmark icon so that other users can trust their appearance is genuine. The verification feature is one of a number of dating safety features being added to Tinder, which will also gain a dedicated in-app safety centre and panic button.