Where does artificial intelligence go next?  - Forbes

Where does artificial intelligence go next? – Forbes

Over the past decade, artificial intelligence has been a relentless source of commercial innovation. Now its influence is about to expand significantly. Once a staple of science fiction, artificial intelligence has been quietly playing a critical role in some of the most ordinary and basic business tasks. business process automation; data analysis; manufacturing defect detection; Essential interactions with customers – all of them are an integral part of modern business and are increasingly being enabled by artificial intelligence.

So where does AI go from here? Even as the pandemic has helped accelerate the shift to cloud computing and remote work, there has also been a wave of innovation preparing AI for its next phase. Many computer scientists, economists, and investors believe we are on the cusp of huge leaps forward in artificial intelligence and machine learning — with implications for both entrepreneurs and companies.

GPT-3 as a model shift

Most applications of artificial intelligence today tend to “train” computers to match images and data so that they can “recognize” new examples of them in different settings. Displaying hundreds of images on a computer, for example, red traffic lights or a potato, allows computer scientists to create applications that recognize these objects and, when necessary, act on them. This type of artificial intelligence is now widespread and we now take it for granted.

The next important step for AI during the worst months of Covid-19 emerged with the launch of OpenAI’s GPT-3 that uses Transformer AI models to enable a computer to not only recognize images and patterns, but actually create language, text, and images on its own.

“This is a paradigm shift,” says Mustafa Suleiman, CEO of Inflection.ai And one of my partners in Greylock. Mostafa previously co-founded DeepMind, which was acquired by Google. “So far, deep learning has mostly been used for classification tasks. These new AI models are capable of creating completely new, high-quality content.

Solomon explains that these Transformer models help computers interact with humans, absorb their language, reference conversations, and then create an entirely new dialogue and language. “These machines will help sort, summarize, and tidy up the huge amounts of information we interact with on a daily basis,” he says.

However, it would be a mistake, he warns, to think of this next stage of AI as merely advancing a single service — for example, generating responses to questions. He believes that one significant achievement of emerging AI technology is that much of it will grow from low-code environments. As a result, language-generating AI will be widespread. “We may soon see a world where every brand builds its own AI system to interact directly with customers.”

Artificial intelligence and business forecasting

Ajay Agrawal, Professor at the University of Toronto, and co-author of the upcoming book Power and Prediction: The disruptive economics of artificial intelligence. He believes that despite significant investment in AI technology, many CEOs remain skeptical about the value. recently cited BCG-MIT . Study which found that while many companies have invested in AI, “most companies still have a long way to go to achieve significant financial benefits.”

However, Agrawal is optimistic about the future impact of AI. While the first wave of AI applications were point solutions that delivered value by “lowering the cost of existing forecasts” such as banking fraud detection and retail demand forecasting, he argues that the second wave will depend on system solutions that “shift production process and possibly value proposition.”

Draws an analogy to the early days of electricity. After years of introducing electricity to cities, only about 3% of American factories were using it. When the new plants realized that distributed electricity not only offered a small cost advantage over fuel or steam, but more importantly allowed them to separate the power supply from the machines, they began to redesign the plants and reposition the equipment in more efficient ways. Electricity use has risen from 3% to 50% in two decades.

Like electricity, AI will change how people perceive what is possible with technology. He believes that the great transformation of AI will occur when business leaders perceive the opportunity not as a fixed solution, but as a path to system-wide innovation.

He explains, “When banks started adopting AI for fraud detection, they just replaced one set of statistical tools for fraud detection with a better set of statistical tools. However, the business has essentially remained the same.” This was easy to implement. The benefits of AI were immediate and measurable. In the coming years, he sees the most ambitious leaders rethink basic questions about the risks they can eliminate.

Consider indoor farming. Until now commercial greenhouses have been largely restricted to pest related risks. With AI-based systems that are increasingly reliable and affordable and that provide early pest detection, a company may decide to triple the size of its greenhouses or invest in a variety of crops.” The catalyst will be the low cost of pest risk forecasting. .

Agrawal believes that the second phase of AI will see many examples where companies from insurance to manufacturing will discover disruptive value propositions based on the fact that AI enables new ways to manage risk through the use of high-accuracy AI predictions. “By using a sensor that can successfully detect and predict leaking pipes, an insurer may do more to help its customers reduce the risk of water damage to homes they expect to be at high risk, even if it means selling policies at lower premiums because of the reduced likelihood of a claim because they can potentially increase the size of the policy. In other words, the next stage of AI is not just an advance in computing power, but something larger that has the potential to impact the strategy, economics, and business frontiers of all businesses. Business strategy will increasingly be shaped by artificial intelligence.

Artificial intelligence as a business tool

Motamady fastMy partner at Greylock, an AI expert, sees the power of prediction and customer interaction coming together in new uses of AI. Like Mustafa Suleiman, he believes that the ability of computers to pre-train on massive data sets will allow computers of the future to solve general problems and fine-tune to take an active role in specific business situations in real time. “The new AI models are excellent at generating information, stream conversations in real time, and rapidly improve upon human responses.”

Al Motamidi sees immediate repercussions on sales, customer service centers, and any interaction between the organization and people. pointing to Kristaa fast-growing company whose AI engines listen in real time to customers, instantly develop insights, and suggest solutions or next steps.

In addition to Cresta, the market has already seen other early efforts to use the AI ​​language generation to solve business problems. jasperAnd the for For example, it generates marketing copy based on limited input about a product; Textio He does the same for creating recruitment materials, developing cultural change, or driving digital transformation under the motto of “enhanced writing”.

Motamedi argues that the combination of language and prediction will make AI relevant to all workflows. He cites cybersecurity, front-office applications, IT, and service management as just some of the areas where core technology will soon be reshaped with AI at its core. Among the practical innovations is the ability to “read” customers through video, act on IT requests, or make predictions in loan application management or creditworthiness. In healthcare, which has always been technically underdeveloped, there is a huge opportunity for artificial intelligence to sort out all kinds of billing and service coding, an area in which the startup is operating Remarkable health You have left a mark with smart automation.

Ongoing Challenges

However, despite all the advances we may see with AI, there are still some intractable and lasting problems that will always be a part of the technology. In a conversation last fall With Greylock’s Reid HoffmanPhi Fei Lee, co-director and co-founder of the Stanford Center for Human-Centered Artificial Intelligence, argues that the deployment of sensors into all aspects of human life raises new questions. “We as technologists are excited to think about how computer vision, smart sensors, and edge computing can help, but we have also faced the issue of privacy, with the question of legal ramifications we never thought of. What if the sensor picks up cases of abuse of care? Could they be Act as legal witnesses or some other hostility event?”

Steve Johnson, IN recent article in New York Times MagazineFind out more controversies about computers capable of generating complete, clear, and original paragraphs on any topic as if they came out of the mind of an educated human. It increases the potential for bots to generate misinformation that appears reliable.

Mustafa Suleiman is aware of the same dilemma. “While AI bots can be good at detecting misinformation, they may also be better at disseminating it at scale,” Lee said.

Sam Motamedi sees these issues as part of the inevitable regulatory oversight that AI will have to accept. “We will all have to confront questions of bias and fairness as we deploy AI to make decisions,” he says. What if a loan is rejected as a result of a machine learning algorithm? He points to TruEra as a company that helps address these questions.

In this context, Ajay Agrawal provides a helpful reminder. Despite advances in computing power, AI remains a tool for prediction, not judgment. Judgment is what humans have to do with predictions served by computing. This remains a good guide as we prepare for more AI in our future.

This future is coming fast. The next era of AI will provide organizations with a much faster time to assess.

But no one doubts that we’ve seen just the tip of the iceberg of AI. Work much more efficiently and automatically generate original content, not just recognizing patterns; democratize forecasting with the potential to disrupt and enable new business models; The exponential increase in new AI-enabled applications will be the hallmarks of the next wave of AI.

(Disclosure: Cresta, Notable Health, and TrueEra are Greylock-backed wallet companies.)

#artificial #intelligence #Forbes

Leave a Comment

Your email address will not be published.