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) …
Identity trust platforms can help distinguish and address different kinds of bots in real-time and ... [ ] without a negative impact on business. Bottom Line: AI shows the potential for thwarting the growing number of bad bot attacks on e-commerce sites and digital channels. Radware finds 58% of bad bot attacks are comprised of distributed, mutating bots that defy easy detection. From selling subscriptions for bad bots to Instacart shoppers willing to pay hundreds of dollars a month in fees to dominating mobile phone providers' contests to capture one of every three prizes, bad bot producers are having a busy year. Cloudflare estimates 40% of all Internet traffic is bot-related.
Aaron Hertzman's Viewpoint "Computers Do Not Make Art, People Do," (May 2020, p. 45) makes excellent points as to why it is very unlikely that computers will ever replace artists. While I don't think he quite stated such, it appears to me that he may be of the opinion that replacement of (natural) intelligence (of human beings) with artificial intelligence is very unlikely. Most, if not all, of the endeavors we are addressing are based on digital technology, and possibly cannot replace analog entities. It is unfortunate, however, that with the hype these days, people are either unaware of reality, or simply ignoring reality, with undesirable consequences. I like to cite a voicemail transcription I received recently.
The subject of AI unrest is really easily proven wrong. While some only have great things to say about AI, there are numerous AI specialists who have taken a stand in opposition to the sort of negative impact of AI that can have on the general public. They also mentioned the analysts to investigate the cultural impacts of Artificial Intelligence. With the increasing use of AI technologies across industries, the important question is, "Will AI replace humans?" In this article, let's find this out.
This paper presents by simulation how approximate multipliers can be utilized to enhance the training performance of convolutional neural networks (CNNs). Approximate multipliers have significantly better performance in terms of speed, power, and area compared to exact multipliers. However, approximate multipliers have an inaccuracy which is defined in terms of the Mean Relative Error (MRE). To assess the applicability of approximate multipliers in enhancing CNN training performance, a simulation for the impact of approximate multipliers error on CNN training is presented. The paper demonstrates that using approximate multipliers for CNN training can significantly enhance the performance in terms of speed, power, and area at the cost of a small negative impact on the achieved accuracy. Additionally, the paper proposes a hybrid training method which mitigates this negative impact on the accuracy. Using the proposed hybrid method, the training can start using approximate multipliers then switches to exact multipliers for the last few epochs. Using this method, the performance benefits of approximate multipliers in terms of speed, power, and area can be attained for a large portion of the training stage. On the other hand, the negative impact on the accuracy is diminished by using the exact multipliers for the last epochs of training.
The debate on AI ethics largely focuses on technical improvements and stronger regulation to prevent accidents or misuse of AI, with solutions relying on holding individual actors accountable for responsible AI development. While useful and necessary, we argue that this "agency" approach disregards more indirect and complex risks resulting from AI's interaction with the socio-economic and political context. This paper calls for a "structural" approach to assessing AI's effects in order to understand and prevent such systemic risks where no individual can be held accountable for the broader negative impacts. This is particularly relevant for AI applied to systemic issues such as climate change and food security which require political solutions and global cooperation. To properly address the wide range of AI risks and ensure 'AI for social good', agency-focused policies must be complemented by policies informed by a structural approach.
EVERY business leader today understands the potential and promise of artificial intelligence (AI). Many of them -- especially those that are ahead of the curve in terms of technology adoption -- are at a stage where they can leverage AI to pioneer exciting use cases. However, charging ahead with the technology has its challenges including inviting scrutiny from regulators, causing concern among customers, and fuelling fear among employees. Facebook, for example, which is at the forefront of innovation with several cutting-edge AI use cases in its labs and on its platforms, seems to have gotten regulators (unnecessarily) concerned. As a result, CEO Mark Zuckerberg and COO Sheryl Sandberg are now looking for ways to assuage fears and charge ahead with implementing and scaling their AI projects.
Trees are a low-tech, high-efficiency way to offset much of humankind's negative impact on the climate. What's even better, we have plenty of room for a lot more of them. A new study conducted by researchers at Switzerland's ETH-Zürich, published in Science, details how Earth could support almost an additional billion hectares of trees without the new forests pushing into existing urban or agricultural areas. Once the trees grow to maturity, they could store more than 200 billion metric tons of carbon. Great news indeed, but it still leaves us with some huge unanswered questions.
Across age groups, U.S. employees believe that paralegals (4%), insurance underwriters (5%), and pharmacists (7%) have the best chance to survive automation; More part time employees (25%) fear that AI will take their jobs within 10 years compared to full-time workers (18%), although there is no significant difference in attitudes on the specific jobs they think are likely to disappear. Employees at the largest companies (with more than 20,000 staff) are slightly less afraid (17%) than the overall group (19%) about the effect of AI/bots on their jobs, possibly because they have already experienced its negative impact (10%), and see a more stable future. Across age groups, U.S. employees believe that paralegals (4%), insurance underwriters (5%), and pharmacists (7%) have the best chance to survive automation; More part time employees (25%) fear that AI will take their jobs within 10 years compared to full-time workers (18%), although there is no significant difference in attitudes on the specific jobs they think are likely to disappear. Employees at the largest companies (with more than 20,000 staff) are slightly less afraid (17%) than the overall group (19%) about the effect of AI/bots on their jobs, possibly because they have already experienced its negative impact (10%), and see a more stable future.
Artificial intelligence (AI) is doing a lot of good and will continue to provide many benefits for our modern world, but along with the good, there will inevitably be negative consequences. The sooner we begin to contemplate what those might be, the better equipped we will be to mitigate and manage the dangers. "Success in creating effective AI could be the biggest event in the history of our civilisation. So we cannot know if we will be infinitely helped by AI or ignored by it and sidelined, or conceivably destroyed by it." The first step in being able to prepare for the negative impacts of artificial intelligence is to consider what some of those negative impacts might be.