Information Technology


[P] Beginner - What to look for • r/MachineLearning

@machinelearnbot

So I'm a .NET developer been doing it for a few years now. AI has always been a seeming interest of mine. Now I've finally found a "Simple", enjoyable and "practical" use for building a system which could utilize a form of Machine Learning. So to give some context; the project is to classify outliers in a large amount of program errors we get on a day to day basis. So, we'll get roughly 100 or so just general errors ranging from "The phone number you used doesn't exist", these are what I'd like to call general errors, or noise.


Demystifying AI, Machine Learning and Deep Learning

#artificialintelligence

Sometimes its ok and good for everyone to un-develop something existing to uncover the hidden gems which are already there and are useful. May be its like Un-Develop to Innovate? Alan Turing published "Turing Test" that speculates the possibility of creating machines that think. In order to pass the test, a computer must be able to carry on a conversation that was indistinctive from a conversation with a human being. AI apart from its traditional definition also includes things like planning, understanding language, recognizing objects and sounds, learning, and problem solving.


Recruiting: AI Bots for Candidate Scheduling

#artificialintelligence

Recruiting has many facets that make up the function. Administrative work is the least desirable facet in my opinion. Scheduling is a huge part of that administrative workload but necessary to keep the engine running. I find myself most productive when I'm performing research/sourcing, on the phone with prospects/candidates, and meeting with clients. That's two-thirds of my activities that require time on my calendar.


Google's self-training AI turns coders into machine-learning masters

#artificialintelligence

Google just made it a lot easier to build your very own custom AI system. A new service, called Cloud AutoML, uses several machine-learning tricks to automatically build and train a deep-learning algorithm that can recognize things in images. The technology is limited for now, but it could be the start of something big. Building and optimizing a deep neural network algorithm normally requires a detailed understanding of the underlying math and code, as well as extensive practice tweaking the parameters of algorithms to get things just right. The difficulty of developing AI systems has created a race to recruit talent, and it means that only big companies with deep pockets can usually afford to build their own bespoke AI algorithms.


Mission-Driven Artificial Intelligence and the Common Good

#artificialintelligence

Humanity is now developing our greatest contribution to the expansion of intelligence on the planet: the flowering of artificial intelligence. It would be a shame if all we used it for were Amazon shopping and Facebook birthday reminders. Luckily, machine learning and artificial intelligence aren't just a for-profit undertaking. Universities, companies, nonprofits, and governmental agencies are already busy developing interesting tools and applications that direct machine learning toward the common good. Though still in their early days, these initiatives just may represent our best bet for addressing our most challenging ecological and societal problems.


A new service would make deep learning more accessible to millions of coders

#artificialintelligence

Google is one of the biggest tech companies paving the way for artificial intelligence and machine learning, and a recent announcement from the company stands to bolster that reputation. This week, Google announced the launch of a new service that will enable both businesses and individuals to begin building their own AI systems. Officially called Google Cloud AutoML, the service comes in the wake of Google's recognition that only a handful of big businesses currently have the budgets necessary to take advantage of AI and machine learning. At the same time, these are often the businesses best positioned to bring on new talent specializing in AI and machine learning engineering. While Google does have pre-trained models, they're typically trained to perform very specific tasks.


[D] What resources for 3D human pose estimation? • r/MachineLearning

#artificialintelligence

Hello, I'm searching for resource for 3D human pose estimation (single person, real time, single or multiple RGB/RGBD cameras). After a bit of research, it seems that the most advanced real-time human pose estimation that is publicly available are Vnect and OpenPose (for single RGB cameras). I am in search for datasets of 3D pose from RGB sequences (PoseTrack seems to be what I need), but would also be interested in RGBD datasets. Do you have any recommendations on the topic? My goal would be to make a quick and dirty model that could take a sequence of RGB frames and output the 3D pose for the frame.


[D] What resources for 3D human pose estimation? • r/MachineLearning

#artificialintelligence

Hello, I'm searching for resource for 3D human pose estimation (single person, real time, single or multiple RGB/RGBD cameras). After a bit of research, it seems that the most advanced real-time human pose estimation that is publicly available are Vnect and OpenPose (for single RGB cameras). I am in search for datasets of 3D pose from RGB sequences (PoseTrack seems to be what I need), but would also be interested in RGBD datasets. Do you have any recommendations on the topic? My goal would be to make a quick and dirty model that could take a sequence of RGB frames and output the 3D pose for the frame.


Why robots need creativity: the year ahead for AI

#artificialintelligence

When our chief executive, Arthur Sadoun, announced that we were going to stash one year's awards cash to fund Marcel's creation, many a jaw dropped. But while we all wait with bated breath for Marcel's first whispers, the project is already a success. Rather than talking, we're doing, trying, trialling. We're on a journey to see how AI can grapple with the complexities of a multinational organisation, where the ultimate product is human creativity. We know we can leverage our creative resources better, it's just way too complex and nuanced to perform through more mechanistic, cruder tools.


Walmart CIO's Priorities: Productizing IT And Process Automation With AI

#artificialintelligence

Clay Johnson has worked at a number of iconic brands, from FedEx to Boeing to General Electric. Roughly a year ago, he joined yet another icon in Walmart. In so doing, he joined a company with 2.3 million associates, 5,000 stores in the U.S. alone, and a complex mix of technology. His priorities in the early days were to meet as many people as possible, to learn the business, and to understand the projects that were ongoing. He has begun to enact a cultural change within the IT department, and he indicates that the four steps he has followed has been to be transparent, to foster open debates, to push everyone to speak up, and to incorporate a fail-fast approach to work.