The key to managing a mountain of data and disruptive technologies may lie in establishing a center of competency.
Although many organizations are using artificial intelligence (AI) and machine language (ML) tools as core enablers in their data analytics projects, and AI spending worldwide continues to rise, the hard truth is that most data science projects are doomed to fail.
There are several reasons for these failures, ranging from the inherent complexity of AI/ML initiatives and the persistent lack of skilled talent to challenges that exist in data security, governance, and data integration. These issues are collectively referred to as concerns for” data readiness,” according to an IDC global survey of more than 2,000 IT and line-of-business decision-makers, all of whom are involved in some level of AI use or development. Read More
Monthly Archives: November 2021
Artificial intelligence that understands object relationships
A new machine-learning model could enable robots to understand interactions in the world in the way humans do.
MIT researchers have developed a machine learning model that understands the underlying relationships between objects in a scene and can generate accurate images of scenes from text descriptions. Read More
Google AI Improves The Performance Of Smart Text Selection Models By Using Federated Learning
Smart Text Selection is one of Android’s most popular features, assisting users in selecting, copying, and using text by anticipating the desired word or combination of words around a user’s tap and expanding the selection appropriately. Selections are automatically extended with this feature, and users are offered an app to open selections with defined classification categories, such as addresses and phone numbers, saving them even more time.
The Google team made efforts to improve the performance of Smart Text Selection by utilizing federated learning to train a neural network model responsible for user interactions while maintaining personal privacy. The research team was able to enhance the model’s selection accuracy by up to 20% on some sorts of entities thanks to this effort, which is part of Android’s new Private Compute Core safe environment. Read More
A Guide to Real World Artificial Intelligence & Machine Learning Use Cases
AI & Machine Learning Will Drive Industry 4.0
This article looks at the ways in which firms across the various sectors of the economy adopt Artificial Intelligence (AI) techniques. However, before we review the sectors affected it is important to note the underlying drivers that are fuelling the growth in the influence and reach of Machine Learning across the sectors of the economy will only grow as we move forwards. This is because Big Data is only getting larger, velocity of data faster, plus the availability of cheaper data storage plus the arrival of powerful Graphical Processing Units (GPUs) to enable Deep Learning algorithms to be deployed. Furthermore, new research in areas of Deep Learning and other Machine Learning areas will continue to emerge into real world production over the next few years leading to new opportunities and applications.
The DLS team strongly believe that the advent of 5G around 2021 will be a transformative and revolutionary moment in human history. The enhanced speed of 5G over 4G will enable technologies, that struggle today with latency requirements, such as virtual reality and autonomous systems, to perform with real time efficiency.
This will be a world of intelligent Internet of Things (IoT) on the edge (meaning on the device) where the data is processed at the place where it is generated and Deep Learning models can run on the device itself rather than on a remote cloud server. This will obviate the need for an autonomous agent such as a robot or vehicle to wait receiving a response from a remote server before it can take an action. Read More
The Father of Web3 Wants You to Trust Less
Gavin Wood, who coined the term Web3 in 2014, believes decentralized technologies are the only hope of preserving liberal democracy.
Do you ever find yourself wondering, “What is Web3?” You’re not alone. The idea is having a moment, whether you’re measuring by VC funding, lobbying blitzes, or incomprehensible corporate announcements. But it can be hard to tell what all the hype is about.
…At the most basic level, Web3 refers to a decentralized online ecosystem based on the blockchain. Platforms and apps built on Web3 won’t be owned by a central gatekeeper, but rather by users, who will earn their ownership stake by helping to develop and maintain those services. Read More
Battle for the soul of a new web
A well-funded and intensely motivated chunk of tech’s hive mind is finding common cause in a vast new project: rebuilding the web on a foundation of cryptocurrency and blockchain tech. They call it “Web3.”
The big picture: Developers, investors and early adopters imagine a future in which the technologies that enable Bitcoin and Ethereum will break up the concentrated power today’s tech giants wield and usher in a golden age of individual empowerment and entrepreneurial freedom. Read More
Facebook is marketing the metaverse, but Apple can make it real
Social media users and the business world now have a general idea of what the metaverse is, thanks to Meta CEO Mark Zuckerberg’s year-long seeding of the term on investor calls and subsequent renaming of Facebook to Meta. Companies as varied as Disney, Bumble, Tencent, the Warner Music Group and others have followed Zuckerberg’s lead by using “metaverse” as a strategic talking point when discussing an internet based on virtual objects and avatars in the coming years. Read More
Cryptographers are not happy with how you’re using the word ‘crypto’
The stadium that is home to the Los Angeles Lakers is getting a new name: the Crypto.com Arena. The name reflects the arena’s new sponsorship agreement with a Singapore-based cryptocurrency trading platform. That may be good news for cryptocurrency fanatics – but perhaps not so much for another faction within the digital landscape: cryptographers.
Look up the word “crypto” in Webster’s dictionary, and you’ll see it refers to cryptography, which in turn is defined as “the computerized encoding and decoding of information”. Search “crypto” on Google, however, and you’ll see a host of top results pointing to cryptocurrencies like bitcoin and ethereum.
This lexical shift has weighed heavily on cryptographers, who, over the past few years, have repeated the rallying cry “Crypto means cryptography” on social media. T-shirts and hoodies trumpet the phrase and variations on it; there’s a website dedicated solely to clarifying the issue. Read More
This Group Pushed More AI in US Security—and Boosted Big Tech
The National Security Commission on AI included members from Oracle, Google, Microsoft, and Amazon. Some of its recommendations are already federal law.
ORACLE, GOOGLE, MICROSOFT, and Amazon are archenemies in the competitive cloud computing market. But in late 2018, top executives from the four companies, including future Amazon CEO Andy Jassy, teamed up on an unpaid side gig: advising the president and US Congress on how artificial intelligence can bolster national security.
The executives were named to the National Security Commission on AI, created by Congress. Its chair was Eric Schmidt, previously CEO of Google, who later said it would help the US “harness this transformative technology to benefit both our economic and national security interests.” Read More
‘Paint Me a Picture’: NVIDIA Research Shows GauGAN AI Art Demo Now Responds to Words
GauGAN2 uses a deep learning model that turns a simple written phrase, or sentence, into a photorealistic masterpiece.
A picture worth a thousand words now takes just three or four words to create, thanks to GauGAN2, the latest version of NVIDIA Research’s wildly popular AI painting demo.
The deep learning model behind GauGAN allows anyone to channel their imagination into photorealistic masterpieces — and it’s easier than ever. Simply type a phrase like “sunset at a beach” and AI generates the scene in real time. Add an additional adjective like “sunset at a rocky beach,” or swap “sunset” to “afternoon” or “rainy day” and the model, based on generative adversarial networks, instantly modifies the picture.
With the press of a button, users can generate a segmentation map, a high-level outline that shows the location of objects in the scene. From there, they can switch to drawing, tweaking the scene with rough sketches using labels like sky, tree, rock and river, allowing the smart paintbrush to incorporate these doodles into stunning images. Read More
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