If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This article is the first in our innovation flywheel series. Future articles will dive deeper into the mechanics of fully scaling the flywheel approach at the enterprise level, with specific focuses on technological and platform evolution, organization and team design, governance, funding, and change management. The pandemic has put the power of digital on full display. Since February 2020, we've witnessed a full-on global embrace of the digital lifestyle. By some estimates, the percentage of grocery shopping conducted online tripled in 2020, the time spent streaming video entertainment jumped by more than 40%, and videoconferencing skyrocketed by over 110%. We've also seen perhaps the most sudden, sharp, and dramatic behavior shift in history with the near-universal adoption of remote and digital work.
Traditionally, only large investors had the resources to invest in the land and professional services critical to reaping the benefits of mineral rights investing in the oil and gas market. Today, artificial intelligence (AI) technology has opened that potentially lucrative industry to individuals with as little as $300 at https://www.investinbraneinc.com. Brane Inc.'s cutting-edge technology is using AI to mine the reams of inefficiently collected, paper-based data of the oil well creation process to determine future well locations. As a result, investors of this technology may benefit from the potentially profitable mineral rights investing activities in these new locations. Although the oil and gas industry experiences price fluctuations common to the commodities market, mineral rights investing for oil and gas have historically generated positive returns for deep-pocket investors.
Microsoft recently open-sourced ZeRO-3 Offload, an extension of their DeepSpeed AI training library that improves memory efficiency while training very large deep-learning models. ZeRO-3 Offload allows users to train models with up to 40 billion parameters on a single GPU and over 2 trillion parameters on 512 GPUs. The DeepSpeed team provided an overview of the features and benefits of the release in a recent blog post. ZeRO-3 Offload increases the memory efficiency of distributed training for deep-learning models built on the PyTorch framework, providing super-linear scaling across multiple GPUs. By offloading the storage of some data from the GPU to the CPU, larger model sizes per GPU can be trained, enabling model sizes up to 40B parameters on a single GPU.
Machine Learning and Deep Learning are concepts that are often overlapping. There can be a slight confusion between the terms, and thus, let us look at Machine learning vs Deep learning, and understand the similarities and differences between the same. Machine learning uses a set of algorithms to analyse and interpret data, learn from it, and based on the learnings, make best possible decisions. On the other hand, Deep learning structures the algorithms into multiple layers in order to create an "artificial neural network". This neural network can learn from the data and make intelligent decisions on its own.
In times of negative interest rates, investors are looking to get out of cash and move to assets that generate returns. Staking could be the answer. Many exchanges provide opportunities to stake tokens and in exchange earn rewards. One can safely earn 5% per annum on a popular digital asset such as ETH. At Modihost we have developed a similar mechanism to staking that rewards buying and holding of AIM tokens.
Cyberattacks continue to grow in prevalence and sophistication. With the ability to disrupt business operations, wipe out critical data, and cause reputational damage, they pose an existential threat to businesses, critical services, and infrastructure. Today's new wave of attacks is outsmarting and outpacing humans, and even starting to incorporate artificial intelligence (AI). What's known as "offensive AI" will enable cybercriminals to direct targeted attacks at unprecedented speed and scale while flying under the radar of traditional, rule-based detection tools. Some of the world's largest and most trusted organizations have already fallen victim to damaging cyberattacks, undermining their ability to safeguard critical data.
Google has worked for years to position itself as a responsible steward of AI. Its research lab hires respected academics, publishes groundbreaking papers, and steers the agenda at the field's biggest conferences. But now its reputation has been badly, perhaps irreversibly damaged, just as the company is struggling to put a politically palatable face on its empire of data. The company's decision to fire Timnit Gebru and Margaret Mitchell -- two of its top AI ethics researchers, who happened to be examining the downsides of technology integral to Google's search products -- has triggered waves of protest. Academics have registered their discontent in various ways.
Artificial Intelligence and machine learning have automated processes, streamlined operations and have also started making intelligent decisions. This proliferation of technology has stoked the fear of cold and calculated robots replacing human interaction. Despite these concerns, a recent study has found that 93% of people are ready to take orders from a robot and more than a third of employees believe that AI will enable better customer and employee experiences. Even then, only 6% of HR teams are actively deploying AI and machine learning solutions. This chasm reveals the missed opportunity for AI to help HR meet evolving employee expectations for a personalised, relevant work environment.
Apple is reportedly planning to come up with an impressive product that brings together its HomePod speaker, FaceTime camera and Apple TV set-top box. A recent report hinted that Apple is working on combining the HomePod speaker with the AppleTV. The technology will come with the FaceTime camera for video conferencing through a connected TV set, according to Bloomberg. With this ambitious smart-home device, users can enjoy watching videos and playing games like when they are using an Apple TV. They can also play music and use Siri, Apple's smart assistant, and have an experience that's similar to what Apple's smart speaker can deliver, sources told Bloomberg.