Think twice before you go and pine over your celebrity crush who might be a digital human.
Hey there, are you daydreaming over your celebrity crush again? Well, it’s time to crash that dream cause the one you are swooning over might not even be a real human. Wait, what? Yes, you read it right. Their beautiful face, pretty eyes, and everything else that is picture-perfect might just be a digital human rendition mastered by some totally grumpy developer-controlled emotionless AI machine.
Guess, who came up with this! Well, who else if not China with their long list of weird AI innovations? In June 2022, a new music video was released by one of the greatest celebrities in China, Simon Gong, getting around 15 million views. But the hawk-eyed fans were not fooled by it. The news was spread quickly that the singer in the video was not actually Simon Gong, but his digital replica made by Baidu. Netizens all over the world are left baffled and confused over the fact that they should be happy over this digital advancement or disappointed over the lack of human touch.
It also raises the question of why is there such a need for digital humans when there is already a population of 7 billion humans. Well, the answer might make you lose sleep; it is the “round-the-clock” services. After 8 or 9 hours of work, a human will need rest as well as food, but these digital humans can work 24×7. From retail to healthcare and finance, the yearning for digital humans is growing to such an extent that experts predict the global market for digital humans will jump to about $530 billion in 2030, from $10 billion in 2023.
Coming back to the Simon Gong case, what makes this digital human different from its other prototypes is its unique interactiveness. The virtual Gong’s digital duties are not limited to singing. On the latest update of the Baidu App, China’s leading search-plus-feed app, Gong appears on users’ phones, helping with searches and queries using the model-actor’s real voice. Since this interactive search experience was launched in 2021, it has boosted the number of voice search queries on Baidu App by 18.2%.
So, think twice before you fall for a ‘digital idol’!!
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AI Systems Are Not Humans! US Court Denies The Patent Right To Machines
US law allows only ‘natural persons’ to be registered as individuals; individuals who can take an oath swearing their paternity to the product
Even as the debate around AI gaining sentience hasn’t subsided, artificial intelligence. US patent court struck down Stephen Thaler’s petition seeking a patent for the products developed by the AI system purportedly developed by him. CAFC, the US appeals court, in Thaler V. Vidal’s case ruled out the machine’s candidature to qualify as an inventor under the US Patent Act. The decision is in similar lines to the series of judgments delivered by courts from around the world for the same case. The legal tiff dates back to 2019 when he filed for a patent for the two products, an AI food container developed based on fractal geometry and a torch light. Instead of using his name in the patent document, he mentioned the neural network’s name, DABUS, claiming that the products are its brainchildren.
Back then US Patent and Trademark Office rejected his plea, reasoning that US laws allow only ‘natural persons’ to be registered as individuals; individuals who can take an oath swearing their paternity to the product, which machines or computer software are incapable of. This time the Court of Appeals, supporting the USPTO’s stand, was unambiguous in stating the obsolescence of “metaphysical matters” about “the nature of invention or rights, if any, of AI systems.” It stressed the repeated reference to the term “individuals” is very well in alignment with its interpretation. “While we do not decide whether an AI system can form beliefs, nothing in our record shows that one can, as reflected in the fact that Thaler submitted the requisite statements himself, purportedly on DABUS’ behalf,” CAFC explained. Cutting the game to chase, the judgment hinges on legal requirements which has little to do with the court’s understanding of AI’s capability.
Refusing to give up on his mission, he wants to contest the judgment in the US Supreme court. He says, “The court ignores the purpose of the Patent Act and the outcome that AI-generated inventions are now unpatentable, will have real negative social consequences.” This brings us to the question if artificial intelligence deserves patent rights and why.
When Thaler says, negative consequences, he means the patent laws being misused under the cover of patent law. For example, AI has been responsible for inventions in the medical field which left unpatented could give leeway to idea hoggers, leaving businesses and funders discouraged to pursue research, preventing cutting-edge research to happen in the first place. Experts too are of the opinion that instead of rewriting the IP Acts completely, it would be a reasonable option to create a custom law including artificial intelligence, because, at the end of the day, AI learns by itself and makes decisions for itself. As artificial intelligence is becoming an omnipresent and inevitable part of day-to-day lives, it is highly imperative to consider if AI qualifies to be considered as an entity similar to a POSA (person with Ordinary Skills in Art). The lack of benchmarks to determine if AI’s invention is unique might be another challenge, given the AI’s ability to constantly improve itself.
This argument finds support in Australian Court’s initial assumptions that led to a favorable judgment only to be overruled later by the appeals court. The judges considered the possibility of AI setting its goal, freedom to choose options and pathways towards the goals, and the ability to trawl for data it requires. The court did spell out why AI’s autonomy is not a misnomer, as long as artificial neural networks can choose the algorithms and interact with other networks. If only this argument could be taken forward to establish AI as a legit entity – which would probably be Thaler’s next line of argument – the question of ‘persona’ could be put to rest.
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Meta Testing Its Latest Chatbot With The Public
BlenderBot 3 can converse informally and respond to the kinds of questions you might ask a virtual assistant
In order to gather input on the system’s functionality, Meta’s AI research laboratories have developed a brand-new, cutting-edge chatbot and are enabling members of the public to communicate with it.
The chatbot is available online as BlenderBot 3. According to Meta, BlenderBot 3 can converse informally and respond to the kinds of questions you might ask a virtual assistant, such as “talking about healthy food recipes or discovering kid-friendly services in the city.”
The prototype bot is based on Meta’s prior work with massive language models, or LLMs, which are capable but unreliable text-generation programs, the most well-known of which is OpenAI’s GPT-3. Like other LLMs, BlenderBot undergoes extensive training on massive text datasets, which it then mines for analytical patterns to produce language. Such systems have proven to be remarkably flexible and have been used for a multitude of activities, such as assisting authors in writing their upcoming best-selling books and producing code for programmers. These models do, however, have serious flaws: they frequently generate user-generated answers and repeat errors in their training data, which is a big problem if they are to function as useful digital assistants.
Meta is particularly interested in using BlenderBot to examine this latter issue. A crucial element of the chatbot is its capacity to look up specific topics online. More significantly, people can click on the answers to see where the information came from by doing so. In other words, BlenderBot 3 can list its references.
By making the chatbot accessible to a larger audience, Meta aims to receive input regarding the various problems that large language models encounter. BlenderBot users can report any suspicious responses from the system, and Meta claims to have made every effort to “minimize the bots’ use of foul language, insults, and culturally insensitive comments.”
For IT businesses, making prototype AI chatbots available to the general public has traditionally been considered a risky step. Microsoft published Tay, a chatbot on Twitter, in 2016. Tay was able to learn from the people it interacted with. As was somewhat expected, Tay soon came under pressure from Twitter users to repeat a variety of racist, antisemitic, and misogynistic sentiments. Less than 24 hours after being notified, Microsoft reacted by pulling the bot offline.
Since Tay’s malfunction, the field of AI has undergone significant development, according to Meta, and BlenderBot includes a variety of safety features that should prevent Meta from making the same mistakes Microsoft did.
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The AI Way Of Making The Right Investment Decision: Ensuring Higher ROI
Even while acknowledging that AI application has business risks and some ethical issues
AI is having a long and highly dynamic intervention in almost every conceivable sphere of our life. It is hardly surprising then that it will also play an increasing role in the entrepreneurial domain, especially in business workflows and processes. Every organization seeking to achieve efficiency and effectiveness looks for appropriate business decisions. In the contemporary era, profitable business decisions to a great extent depend on high-tech applications, especially AI. But experience reveals that one cannot do it in a mechanical way. There is, for instance, a clear signal that approaching AI for short-term business capabilities seems to be paying more dividends than leveraging it as a research and development agency. So, the right kind of investment matters.
There is no doubt that in contemporary times there are a plethora of business strategies from which an organization can opt for ones according to its needs. Now we are well into the Information Society and the generation and maneuvering of data have become crucial for the success of any organization. But to repeat, the process of organizational change based on the adoption of new technology cannot be mechanical. Accumulation of mere data does not lead the organization anywhere as information overload is bad for the organization’s health. The AI can come to the rescue here with its up-end software to integrate the solution with the existing business architecture of a specific organization, without disturbing the business process and workforce. The best way to do it is to develop a comprehensive picture of the business process and workflows, rather than adopting what till now has been predominant, a sectoral approach in which an organization is perceived in terms of ‘slices.’ The AI-sourced ‘overall’ picture is being built up with as many components as product and/or service development, manufacturing, service operations, human resources, marketing and sales, supply chain management, risks, strategy, and so forth.
Modern organizations are invariably complex organizations. If the business process and workflows are ‘sliced’ and perceived in terms of separate compartments the outcome has a high chance of getting complicated and futile. AI algorithms are now facilitating organizational management by making available reliable structured reports based on real-time actionable data. Various reports mention that AI adoption is highest within the product-or service-development and service-operations functions.
AI software has become so sophisticated that it is causing the end of the days of trial-and-error methods with extremely precise predictability. AI is at the same time giving rise to ‘smart’ communication with astonishing exactness for the intended users of the organization. With AI reaching such heights in organizational life and its business domain its predictive capacity is also combined with prescriptive capability, which in turn induces organizations to break the glass ceiling. According to a McKinsey’s global survey, published in a report titled The State of AI in 2020, the largest share of respondents reports revenue increases for inventory and parts optimization, pricing and promotion, customer-service analytics, and sales and demand forecasting. More than two-thirds of the respondents who report adopting each of those cases affirm that its adaptation has led to increased revenue. Over half of the respondents who report adopting each of that mention that the use of AI in those areas reduced costs. Such developments have special significance in the post-COVID 19 pandemic world and its transformation imperatives. According to an IBM report, negotiating the disastrous effects of the pandemic AI continues to enable organizations to address urgent and immediate business priorities—quickly and at scale. The report notes that AI improves a company’s cost base—augmenting human capability to motivate greater and more expansive efficiencies. It is also stated to help enhance or protect top-line revenue, experience, and engagement. The report’s six-year data series shows that COVID-19 has accelerated AI’s shift from experimental to widely adopted as a key lever of sustainable competitive advantage and profitability across businesses and industries around the world.
Even while acknowledging that AI application has its risks and some ethical issues, the fact remains that the right investment in AI goes on to benefit an organization.
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