Top 6 AI Model Quality Trends To Watch Out For In 2023
The top 6 AI model quality trends to watch out for in 2023 are essentially enlisted in this article
We can expect to see a continued spotlight on these top 6 AI model quality trends in 2023 and help companies achieve a return on their growing AI investments. anticipate more public relations disasters that could have been avoided with improved AI model quality trends
The top 6 AI model quality trends in 2023:
A Movement Towards More Formal Testing and Monitoring Programs for AI models: Similarly, to software development 20 years ago, business software use did not take off until testing and tracking became commonplace. Intelligence is approaching a comparable tipping point. Machine learning and artificial intelligence technologies are rapidly being accepted, but their quality differs. Often, the data scientists who create the tools are also the ones who physically evaluate them, which can result in blind spots. Manual testing is time-consuming. Surveillance is new and haphazard. And the quality of AI models is extremely variable, becoming a deciding element in the effective adoption of AI. Automated testing and tracking ensure quality while reducing ambiguity and risk.
AI Model Explainability stays Hot: As AI becomes more prevalent in people’s daily lives, too many people want to understand how the algorithms function. Internal partners who need to believe the models they are using, consumers who are affected by model choices, and authorities who want to ensure that consumers are handled equitably are driving this.
More Debate about AI and Bias. Is AI a Friend or Foe of Fairness: People were concerned in 2021 and 2022 that AI was creating bias due to variables such as poor training data. In 2023, I believe there will be an increasing awareness that AI can eliminate prejudice by avoiding the historical moments where bias was present. People are frequently more biased than computers; we are beginning to see methods for AI to minimize bias rather than add it.
More Zillow-like Debacles: Until testing and tracking become common practice, businesses will continue to battle with quality problems such as the ones Zillow encountered in its home-buying section (Old versions cause the business to overbuy at exorbitant rates, eventually leading to the division’s closing and huge losses and unemployment). In 2023, I anticipate more public relations disasters that could have been avoided with improved AI model quality methods.
A New Vulnerability in the Data Science Ranks: There has been a serious dearth of data scientists for several years, and businesses that have them have treated them like treasures. However, as the difficulty of showing ROI on AI efforts continues, and as the economy softens, businesses are adopting a tougher stance on outcomes. Only one out of every ten models created currently is used in production. Data science teams that are unable to rapidly deploy models into production will experience increased strain. Those positions may not be safe indefinitely.
Formal Regulation of AI uses in the U.S.: Unlike the European Commission, US governing agencies have been studying the challenges and effects of AI but have yet to make a major move. That will change in 2023 when the United States will eventually write its federal regulations, similar to those already in place in the EU and Asia. Guardrails benefit everyone in this market and will eventually help create confidence in AI. Regulations in the United States are not far away, and companies should prepare. The latest White House Blueprint for an AI Bill of Rights, which was published in October 2022, is a move in the correct direction, offering a foundation for responsible AI creation and use.
The post Top 6 AI Model Quality Trends to Watch Out for in 2023 appeared first on Analytics Insight.
‘AI-based’ dApp Harvest Keeper drains millions in users’ funds
- Recent reports suggest that AI-powered dApp Harvest Keeper is a rug pull scam.
- Several crypto security firms, including CertiK, claimed that the project has stolen nearly $1 million.
According to recent reports, the “AI-based” dApp Harvest Keeper is a rug pull scam.
On 19 March, CertiK, a crypto security firm, reported that a privileged getAmount function drained the Paris-based Harvest Keeper smart contract. It was also discovered that users’ assets were stolen through ice phishing transactions on Binance Smart Chain [BSC], Ethereum [ETH], and Polygon [MATIC].
We can confirm that @Harvest_Keeper is a scam.
At the time of writing, we can confirm ~$933k of users’ assets have been stolen.
Revoke permissions to EOA: 0x250ce5a8d8a8f0345fb8708e0575c8ede7710c14
Do not interact with the project’s URL. pic.twitter.com/MeQRSeydND
— CertiK Alert (@CertiKAlert) March 19, 2023
Several crypto security firms, including CertiK, claimed that the project has stolen nearly $1 million. Individuals have been advised not to interact with any of the project’s URLs.
The security division of De.Fi also requested that users revoke smart contract approvals as soon as possible.
There has been no evidence of the attacker’s identity so far. However, since the theft has taken place so recently, it is possible that the identity will be discovered later.
Ice phishing is a web3 attack that tricks users into manually signing and approving permissions. The rug pull is another such crypto scam.
Across the three aforementioned chains, $219k has been stolen in ice phishing transactions so far.
2/ At the same time, user assets have been stolen through ice phishing transactions across BSC, Ethereum and Polygon.
Across the 3 chains, ~$219k have been stolen in ice phishing transactions so far.
Stolen assets transferred to EOA 0x15a8a.
— CertiK Alert (@CertiKAlert) March 19, 2023
Taking advantage of enthusiasm around AI
Harvest Keeper claimed to use artificial intelligence (AI) in such a way that users could receive daily rewards of 4.81%, with the investment increasing to 101% in three weeks. The project promoted itself as a platform that could assist users in turbulent market conditions by utilizing AI.
Harvest Keeper also claimed that Contract Wolf tested its smart contract, confirming the complete safety of investments and the absence of technical flaws in the platform’s work.
To some extent, the enthusiasm around AI has taken over the crypto market, with many related projects experiencing rapid growth. Harvest Keeper appears to have taken advantage of this.
The crypto community is understandably enraged by the news. In any case, investors will have to put up a fight to get back their funds, which is a common theme running through the market as it experiences many negative incidents.
Report: China Will Become A Metaverse Tech Leader During 2023
A report issued by Globaldata, a global consulting and data analysis company, predicts that China will become a leading country in metaverse tech during 2023. The firm believes that the development of other technologies like artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and 6G will allow China to configure itself as a metaverse hub.
China to Lead Metaverse Industry in 2023
While the interest in the metaverse seems to be waning at a worldwide level, China is still pushing to become a leader in the industry. According to a recent report prepared by Globaldata, a consulting firm, China is positioning itself to surpass the West when it comes to metaverse tech, as the country will keep investing in technologies related to this field.
The report states the importance that China gives to these accessory technologies will allow it to become a center for the metaverse. It states:
The growing emphasis on VR, AR, AI, and 6G aims to outpace advances in the West and position China as a global hub for the metaverse.
Furthermore, Globaldata believes that there are signs that indicate that China will continue to invest in virtual reality and artificial intelligence with the objective of promoting the economic development of the nation. Several Chinese provinces and cities have already presented plans to become metaverse tech hubs, including Shanghai and Zhejiang among them.
Where Will the Metaverse Go?
While the metaverse is commonly associated with software and hardware dedicated to the consumers, the report proposes the Chinese metaverse is likely to focus more on the industry and the benefits that it can reap from including metaverse tech in its processes.
The Chinese Ministry of Industry and IT recently released a report on the application of VR and metaverse tech into industrial processes, showing how these can be mixed efficiently. Globaldata predicts the metaverse will be more appreciated than other technologies due to the possibilities it presents. On this, it explains:
Chinese investments in metaverse-related technology will highlight the value of the metaverse compared to existing one-off experiences such as social media, gaming, or ecommerce.
However, even with estimations that put the metaverse sector value at $376 billion by 2025, 2023 is described as a year in which investments in the metaverse will suffer a cool-down phase, product of the “cooling interest, economic obstacles, and the immaturity of enabling technologies.”
Tags in this story
Artificial Intelligence, Augmented Reality, China, globaldata, industry, IT, Metaverse, report, Shanghai, West, Zhejiang
What do you think about the prediction that puts China over the western world when it comes to metaverse investments? Tell us in the comment section below.
Sergio is a cryptocurrency journalist based in Venezuela. He describes himself as late to the game, entering the cryptosphere when the price rise happened during December 2017. Having a computer engineering background, living in Venezuela, and being impacted by the cryptocurrency boom at a social level, he offers a different point of view about crypto success and how it helps the unbanked and underserved.
Image Credits: Shutterstock, Pixabay, Wiki Commons
AI Be Used In Voice Cloning
How Can AI Be Used In Voice Cloning?
Artificial Intelligence in Voice Cloning is an interesting way to use the technology
Artificial Intelligence has rapidly made its way, you name it and Artificial Intelligence (AI) is everywhere.
The article mentions how can AI be used in Voice Cloning.
AI can easily copy a voice by understanding the patterns of vocal cord vibration that result in particular sounds. Then, new, comparable sounds that can imitate the original voice are produced using these patterns. Artificial intelligence (AI) is used in voice cloning technology to imitate a person’s voice. Neural Networks can help a lot in AI Voice Cloning.
With the aid of this technology, it is possible to duplicate someone’s voice or produce a new voice that is similar to the original. Creating artificial voices for digital assistants, making voiceovers for movies and video games, and developing new voices for communication devices are just a few of the many uses for voice cloning.
Although several methods can be used for voice cloning, in my opinion, neural networks are the finest.
Why Neural Networks, You Ask?
Because it is just like a brain like a human brain, which has millions and billions of neurons that receive the signal from various senses, assist the brain in decoding them, and then assist in assisting the body in reacting following the signals, similarly, Neural Network is an artificial brain, which has millions and billions of neurons, which assist in decoding the signals and assisting the machine in reacting.
Neural networks come in three main categories:
Synthetic neural networks (ANNs), Recurrent neural systems (RNNs), and Convolutional neural systems (CNNs).
The simplest kind of neural network is an ANN. A hidden layer, an output layer, and an input layer make up each of them. The hidden layer handles the calculations, the input layer takes in the inputs, and the output layer generates the outputs. RNNs are akin to ANNs, but they also contain extra layers that let them interpret data sequences. As a result, they excel at tasks like speech recognition, and machine translations are built with image processing in mind.
Some convolutional layers, an output layer, and an input layer are all present.
The output layer creates the results after the convolutional layer’s extract features from the images.
Hence AI Has reached a point where it can be used for many purposes.
The post How Can AI be Used in Voice Cloning? appeared first on Analytics Insight.
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