Collaborating Authors

How to catch up on Metroid, the classic series shunned by Nintendo

Washington Post - Technology News

If you're new to the series, I would not recommend playing the Nintendo original, available free as long as you're a paying Nintendo Switch online subscriber. While it was a milestone, it hasn't aged as well as Nintendo's other titles, like the first Mario or Zelda games. If you insist on starting in chronological order, then you should hunt down the 2004 remake for the Game Boy Advance, "Metroid: Zero Mission." Without a Game Boy Advance, you can buy the game off the Wii U shop. "Zero Mission" is a reimagining and streamlining of the first game, and has become a staple in speedrunning competitions over the years, thanks to many deliberate new design changes.

Council Post: The New Normal: Reimagine The Transformation Of Industries With AI


Just a decade ago, you would gloss through a TV Guide or ask a friend to recommend a new series worth watching. Cut to today; Over-the-top (OTT) platforms are equipped with a lot more data mining and understanding of viewers' preferences to make personalized show recommendations. AI-led recommendation engines have truly revolutionized how we consume content, and OTT is not the only segment that has undergone such a transformation. With its far-reaching impact across industry segments, AI has unleashed the Fourth Industrial Revolution and is changing business processes as well as how industries reimagine their customer's preferences. Many AI companies have been at the forefront of this transformation, making an impact on clients' businesses and processes.

EU privacy watchdogs call for ban on facial recognition in public spaces


BRUSSELS: Europe's two privacy watchdogs teamed up on Monday (Jun 21) to call for a ban on the use of facial recognition in public spaces, going against draft European Union rules which would allow the technology to be used for public security reasons. The European Commission in April proposed rules on artificial intelligence, including a ban on most surveillance, in a bid to set global standards for a key technology dominated by China and the United States. The proposal does allow high-risk AI applications to be used in areas such as migration and law enforcement, though it laid out strict safeguards, with the threat of fines of as much as 6per cent of a company's global turnover for breaches. The proposal needs to be negotiated with EU countries and the bloc's lawmakers before it becomes law. The two privacy agencies, the European Data Protection Board (EDPB) and European Data Protection Supervisor (EDPS), warned of the extremely high risks posed by remote biometric identification of individuals in public areas.

Artificial Neural Network is Revolutionizing The Future of the Translation Industry


Do you know that a full-time working translator can translate approximately 520,000 words per year? There would be no wrong in saying that the translation industry has existed for centuries and will progress in double digits in the upcoming years. Because digital realms continuously push for more shared and globalized experiences, the current worth of the global translation industry is $56.1 billion, and the figure is expected to increase at a swift pace in upcoming years. The number is projected to surpass $70 billion by the year 2023. It's been more than 10 years since the launch of Google translate by utilizing phase-based machine translation algorithms.

Build an Application Digital History using Natural Language Processing


With the historical text data, images data or speech data, we can build an application that will help to understand the historical terms more effectively and will also broad line the visuals if needed. Using Natural Language Processing techniques like named entity recognition, part-of-speech tagging we can aim for text summarization with the clear perspective of explaining the historical terms. The report can be generated which could be further utilized for analysis for specific incident or event. During learning history, I felt hard to pronounce the names of kingdom and rulers. Thus, we can apply, listen and speak button for difficult words in the document.

A Comprehensive Guide to Ensemble Learning - What Exactly Do You Need to Know -


Ensemble learning techniques have been proven to yield better performance on machine learning problems. We can use these techniques for regression as well as classification problems. The final prediction from these ensembling techniques is obtained by combining results from several base models. Averaging, voting and stacking are some of the ways the results are combined to obtain a final prediction. In this article, we will explore how ensemble learning can be used to come up with optimal machine learning models. Ensemble learning is a combination of several machine learning models in one problem.

Hewlett Packard Acquires AI Company Co-founded by Machine Learning Professor

CMU School of Computer Science

A machine learning technology company co-founded by Ameet Talwalkar, an assistant professor in the Machine Learning Department at Carnegie Mellon University's School of Computer Science, will join Hewlett Packard Enterprise (HPE). Determined AI, a San Francisco-based startup, builds software that trains artificial intelligence models more quickly and at scale using its open-source machine learning platform. Talwalkar is chief scientist at Determined AI, which he co-founded in 2017 with Neil Conway and Evan Sparks. "We are thrilled about the opportunity to partner with HPE to deliver co-designed software and hardware and tackle some of society's most pressing challenges," the founders wrote in a blog post announcing the acquisition. "HPE shares our vision that driving an open standard for AI software infrastructure is the fastest way for the industry to realize the potential of AI."

This self-emptying Shark robot vacuum is one of the best Prime Day deals we've seen


Save $150: The Shark AV911S robot vacuum with a self-emptying base is at its best price ever of $349.99 at Amazon as of June 22 for Prime Day. If you skipped spring cleaning this year, we don't blame you. But you'll now look pretty smart since that means you get to enjoy all of Amazon's top robot vacuum deals for Prime Day. So if you procrastinated on cleaning duty, then prepare to save big on high-end options such as this advanced Shark robot vacuum. SEE ALSO: Eufy's quiet and thin RoboVac 11S is $90 off this Prime Day Perfect for anyone who wants to handle dirt as little as possible, the Shark AV911S EZ robot vacuum with a self-emptying base is down to just $349.99 at Amazon.

British-built solar powered drone can fly at 70,000ft for a YEAR

Daily Mail - Science & tech

A British-built solar powered drone with a 115ft wingspan that can stay in the air for over a year will be an alternative to low Earth orbit satellites, its developers claim. PHASA-35 is a cutting edge drone being developed by BAE systems at their facility in Warton, Lancashire that can fly about at 70,000ft above the surface for 20 months. It harnesses power from the Sun to stay airborne, charging a bank of small batteries during the day to keep it flying overnight, allowing for longer operations. The 150kg drone is able to carry a payload of up to 15kg including cameras, sensors and communications equipment to allow troops to talk to each other or provide internet access to rural locations during a natural disaster or emergency. BAE systems say it will be available by the middle of the decade and provide a'persistent and affordable alternative to satellite technology.'

Deploying ML Models to the Edge using Azure DevOps


Training ML Models and exporting it in more optimized way for Edge device from scratch is quite challenging thing to do especially for a beginner in ML space. Interestingly Azure Cognitive Services will aid in heavy lifting half of the common problems such as Image Classification, Speech Recognition etc. So in this article, I will show you how I created a simple pipeline(kind of MLOps) that deploys the model to an Edge Device leveraging Azure IoT Modules and Azure DevOps Services. Blob Storage – For storing images for ML training 2. Logic Apps – To respond Blob storage upload events and trigger a Post REST API call to Azure Pipelines 3. Cognitive Services – For training Images and generate a optimized model specifically for edge devices. Containerized Az Devops Agents will be running inside this, orchestrated using K3s Kubernetes Distribution.