Can Artificial Intelligence Reverse The Tech Downturn? Startups Are Hiring For The Next Big Thing.

In San Francisco's Hayes Valley neighborhood — a hub for Artificial Intelligence that's been nicknamed "Cerebral Valley" — more than 200 AI experts on artificial intelligence met in late March to discuss the white-hot technology and how to build businesses around it.

"The general sentiment was this is something that can be incredibly useful and dangerous. It is happening, and it is unstoppable," said Evan Buhler, co-founder and CEO of Generative Counsel, a San Francisco-based startup.

"I moved to the Bay Area in January from Florida to be part of something special," Buhler told MarketWatch. "It almost feels like destiny. AI could become the economic and spiritual center of San Francisco. Cerebral Valley has this community and edge on everywhere else because it is where the flow is."

Chooch, a startup that released a mobile AI app this week, says 15 people have joined the company over the last three months, most of them from outside California and some from outside the U.S. The AI surge has been a "beacon of light for the tech world" after months of shrinking market valuations, declining ad spending, layoffs, high interest rates, a turbulent economy and the immolation of Silicon Valley Bank, Chooch CEO Emrah Gultekin told MarketWatch. Chooch now employs 73 people.

And artificial intelligence isn't just fueling a return to San Francisco — it's also drawing millennials to AI tech hubs around the country as they seek to be part of the next big thing. Venture-capital firms and large tech companies are pouring billions of dollars into AI technology. There were nearly 800,000 AI-related job openings in the U.S. Last year, led by California's 142,000, according to data collected by Stanford University's Institute for Human-Centered Artificial Intelligence — and the pace appears to be accelerating.

Meanwhile, although the San Francisco Bay Area lost 53,000 residents last year, that was less than one-third the number of people who left in 2021, according to data released by the U.S. Census Bureau last week.

On Thursday, Garry Tan, CEO of startup accelerator Y Combinator, said that more than 80% of the startups in his company's latest batch were based in San Francisco, and many of them are working on AI.

Despite a significant drop in venture funding and deals in the first quarter of 2023, AI is continuing to prove alluring to investors. Last month, a $150 million investment in startup Character.Ai, led by venture-capital firm Andreessen Horowitz (known as a16z), gave the startup a value of $1 billion.

The median pre-money valuation for generative-AI firms has catapulted to $90 million in 2023 from $42.5 million in 2022 , based on nine deals PitchBook tracked through March 29.

"The settlers are scrambling for their 40 acres [of digital land]," said Charley Moore, the CEO of Rocket Lawyer Inc. Who is a longtime participant and observer in Silicon Valley. "Tech can have something of a herd mentality, and AI has captured some of the crypto zeitgeist." (Before AI, crypto was all the rage in tech, prompting a land rush of its own before it recently cooled down.)

California isn't the only destination for would-be AI entrepreneurs. Texas, New York and Florida are other big hubs, according to the Institute for Human-Centered Artificial Intelligence.

Appian Corp. A cloud company in Tysons, Va., with AI apps, plans to hire 600 to 700 workers this year after adding 800 last year, bringing its total head count up to 2,300. And AI startup All Turtles, which decamped to Arkansas from San Francisco in late 2020, continues to hire steadily, CEO Phil Libin told MarketWatch.

Still, the surge in AI development has brought some millennials who left during the pandemic back to the Bay Area. At the SXSW tech conference in Austin, Texas, in March, "this came up a lot," Muddu Sudhakar, chief executive of AI startup Aisera, told MarketWatch. "People said they were returning to the Bay Area to be part of the AI revolution."

He added: "ChatGPT was the talk of every session, every discussion, and young people want to be in the middle of the action. It was like the gold rush."

Also read: Biden meets with advisers on 'risks and opportunities' in AI technologies

"AI is hot everywhere," said John Chambers, the former CEO of Cisco Systems Inc. Whose firm JC2 Ventures backs more than a dozen AI startups. "It is the third major frontier during my time in tech, and it will be bigger than the first two — the Internet and cloud."

Debasish Biswas, the chief technology officer at AI data platform Aware, which is based in Columbus, Ohio, said engineering job applications are in the hundreds, up threefold from the previous quarter. Many of them are from job seekers based in the Seattle area and Silicon Valley and from the ranks of current and former employees of Big Tech companies such as Alphabet Inc.'s Google, Amazon.Com Inc. Salesforce Inc. And Facebook parent Meta Platforms Inc. — all companies that have announced layoffs in recent months.

"People would rather work on solutions used by top brands rather than many layers away from activity," Biswas told MarketWatch.

Also read: U.S. Economy added jobs again in March. Is this your last chance to jump ship?

Kira Makagon is the chief innovation officer at cloud software company RingCentral Inc. And leads the company's AI efforts. She said the recent rounds of layoffs and the current economic crisis have prompted tech talent to "make and do some fun things" at fledgling AI startups.

Indeed, the bloviation over AI — nearly every major tech CEO has embraced the technology and hyped their own offerings the past few months, often during quarterly earnings calls with analysts — has added to a three-ring-circus atmosphere that seems concentrated in the San Francisco Bay Area.

"We're just at the start of AI," Appian CEO Matt Calkins told MarketWatch. "There is the classic hype cycle versus trust debate at work here. AI is a tool, not a replacement. And there will be a roller coaster for at least six months."

Also read: The 'explosive' AI trend is here to stay. These stocks are poised to benefit.

And: 'Should we risk loss of control of our civilization?' Elon Musk, Steve Wozniak and other tech leaders ask in petition to halt AI development

The Long Quest For Artificial Intelligence

Ever since computers were invented to automate some manual tasks, there has been a quest to mimic the way the human brain works — to create some kind of human intelligence using computers.

The effort had a long gestation period of about five or six decades. As a result, artificial intelligence, or AI, as it is known, dominates various aspects of our day-to-day lives.

AI has developed in different directions. While proving to be a boon overall, it is stoking fears of surpassing human intelligence.

For a long time, AI was always around the corner, like nuclear fusion has been for several decades, and even is today. Along the way, we reached a stage where AI became a distinct possibility, and the best we could hope for was fuzzy logic, which did make its way into gadgets like washing machines to optimise their performance.

Two things happened that made current AI a reality.

First is the progression of Moore's law, which resulted in computer chips doubling in performance every 18 months. As a result, we now have the most powerful computer in our pockets in the form of our smartphones, which are orders of magnitude more powerful than the ones which guided the Apollo spacecraft to the Moon.

The second development is collection of huge amounts of data via the technology platforms: Facebook, Google, Twitter, Microsoft, Amazon, Apple, IBM, Tencent, Alibaba, and others.

Data has been collected to indicate the preferences and activities of billions of people in the world — all this in the name of offering freebies in terms of allowing free search and communication abilities. This is akin to politicians garnering votes by giving away cheap gifts. A lot of data is also being collected by the digital payment platforms.

Armed with these two developments, there is enough computing power and data available to the technology companies to look for hidden patterns within the data, which would not have been humanly possible to do previously.

Thus, we have "big data" and the software algorithms known as "deep neural networks."

Regardless of the buzz words, it led to recommendations of books and other products on e-commerce platforms, in filtering out search data and topics for users to consume, identification and discarding of spam emails, and so on.

Translation between languages has been another great success story for AI.

While on a recent visit to Panama, we used the phone to type in an English phrase and it translated to Spanish, which we then showed to the local folks. They then typed in Spanish responses on their phones and translated to English and showed us their phones. This strategy came to my rescue whenever my broken Spanish did not work.

Assistants like Amazon's Alexa and Apple's Siri started to recognise human language and respond back. Video recognition is leading to self-driving cars. More the humans interact with AI, the more it learns, like human babies, and the more it grows. It needs computing power and lots of data as key ingredients. But it is still a human-initiated exercise. The AI is not acting by itself.

AI was used to beat the human world chess champion, the human Jeopardy champion (a quiz show in the United States), the human Go champion (South Korean board game).

Chess and Go are strategy games based on a lot of permutations and combinations, while Jeopardy is a knowledge-based game. AI has now reached a stage in this process of learning the rules of the game by itself, instead of being fed by humans. In a technique called "reinforcement learning," AI learns by trial and error. AI has learnt new games by itself.

Other than capturing data from customers, there are a lot of sensors in various types of machinery and CCTV cameras all over. The data gathered from these sources, coupled with cheap storage devices, means that we are drowning in data.

The data management software is freeware in most of the cases. The data can be stored and processed in the cloud without owning any piece of hardware or software. This is a bonanza for AI, which can predict when a machine will break down or is in need of parts replacement. Or try to recognise a suspicious personality from hundreds of CCTVs footage.

AI is being used in diverse applications like drug discovery in the pharma industry — to find the right chemical molecule from millions of combinations to fight a particular disease. It is also being used to analyze and decode the Sumerian script — the ancient writing thousands of years old from Mesopotamia.

The most recent applications to capture the headlines are ChatGPT and DALL-E. Both of them are from OpenAI.

ChatGPT is a large language model which can analyse millions of documents and summarise on a particular topic or an issue or a question.

Similarly, DALL-E can draw a picture based on clues supplied via text. It's like an artist working for the police who can draw the picture of a suspect based on the description supplied by witnesses.

As a result, Microsoft has invested $10 billion into OpenAI to get a headstart on this technology and use it in their products.

Both these tools are freely available for anyone to play around with. Essays are being written and pictures generated by lay people with no experience in doing so. I make the claim that I wrote this article without the help of any of the tools out there.

Such tools are part of Generative AI, leading towards what is called AGI (artificial general intelligence).

All the current AI capabilities of interpreting data and coming to conclusions is more like a domain-specific AI. The domains can be drug discovery or language transalation. It cannot be expected to solve general problems in another domain or across domains.

AGI is far out into the future. Generative AI is a possible bridge towards that goal.

Regarding the feared dangers posed by AI, I don't see a possibility of AI overtaking humans or human intelligence, even if AGI becomes a reality and comes to dominate our lives.

AI will grow while humans will evolve to work with AI in a collaborative way. Technological advances will gallop with convergence of multiple technologies, and human lives will be different in the future, but not as slaves or the haunted ones.

Artificial Intelligence: How To Turn Conversational AI Into A Success Business

Boris Kontsevoi is a technology executive, President and CEO of Intetics Inc., a global software engineering and data processing company.

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AI used to be the stuff of sci-fi movies, but now it's all around us—computer vision and chatbots have become part of the standard business processes. Recently, artificial intelligence has reached its peak and made a breakthrough that has affected almost every industry, from high tech, telecoms, finance and healthcare to pharmaceuticals. The global AI market is expected to grow by more than $500 billion between now and 2030, according to various studies. IDC, a market research firm, predicted that the AI market will be worth over $500 billion by 2024. Let's figure out why.

The Story Behind AI: When It Was Started

The history of modern AI began in 1956 at a computer workshop at Dartmouth College (New Hampshire, USA), where the term "artificial intelligence" was coined by John McCarthy.

In the late 1950s and early 1960s, AI research primarily focused on developing systems that could mimic human minds: symbolic AI and connectionism (initial neural networks). It appeared to be more complicated, and government financing was cut off in 1974. Then during the 1980s, the focus shifted to the creation of problem-solving expert systems.

Yet, following Lisp machine's collapse in 1987, the second AI winter began. In the 1990s and 2000s, the research revived artificial neural networks. Today, faster computers, new algorithms and the availability of large amounts of data have enabled systems that can interpret complex data, learn autonomously and make near real-time decisions.

But Where Do Concerns About The Reliability Of AI Come From?

Conversational AI and virtual assistants are designed to simplify our daily lives by taking care of tasks that we may find tedious, time-consuming or complicated. They are serving us 24/7—without productivity losses—by understanding and responding to our requests using NLP and machine learning algorithms. Where there are huge advantages, there are also risks, as the whole AI system is vulnerable to any weaknesses or biases in the underlying system that underpins it.

Generative technologies have the potential to facilitate the production of disinformation for big fans of conspiracy theories or propaganda messages. They can also serve as a source of information search for people who do not have a highly developed criticality of the information. Finally, nothing is perfect. Remember how you used to Google information for research? Did you trust all the sources you found? Probably not, but artificial intelligence is highly trusted. Is there a good reason for this?

You Reap What You Sow

We are familiar that AI is capable of processing large volumes of data in a short period of time and formulating predictions based on patterns identified in the data. However, their ability to comprehend the larger context or comprehend the nuances of a given situation may result in misinterpretation. AI systems only work as well as the data they're trained on. If that data is skewed or incomplete, then the AI's output will be biased and incomplete, too. Moreover, from a limited perspective, in certain circumstances, AI may be given excessive autonomy and control without adequate human supervision. This can result in unforeseen or detrimental consequences that were not anticipated.

Despite the material written above, artificial intelligence is still strongly trusted. According to a McKinsey survey, "more than two-thirds of consumers say that they trust products or services that rely mostly on AI as much as, or more than, those that rely mostly on people."

Unlocking The Full Potential Of Conversational AI For Your Business

Whether you run a business, you are a consumer or both, you want to get the most out of your interactions with machines and humans. No matter what industry you work in, conversational AI can be integrated into various platforms, such as messaging apps and voice assistants, making it accessible to users. It allows companies to automate customer service, personalize communications and collect valuable data. Conversational AI is used by a wide range of businesses, organizations and individuals across various industries, including customer services, healthcare, e-commerce, education and financial sectors.

AI As A Successful Business Model

There are several key steps to developing a successful conversational AI business model. The first step is to define a niche, then create a high-quality product that can communicate naturally, understand complex queries and provide accurate answers. In addition, the AI machine must have the ability to support a large number of users and be trained with machine learning algorithms.

Secondly, NLP tools may be needed to enable conversational AI to understand natural language queries and provide accurate responses. Integration with existing systems such as customer relationship management (CRM), enterprise resource planning (ERP) and help desk software can greatly enhance the capabilities of a conversational AI product. This can help streamline customer support, streamline workflows and provide a more personalized customer experience.

Finally, the last step is to create a go-to-market strategy. This strategy should include defining the target audience, analyzing the needs and preferences of the target audience and developing a marketing plan to target them. This strategy may include creating a website, advertising and content marketing or attending trade shows. Conversational AI systems should be regularly monitored and optimized to ensure that they meet users' needs and solves their problems. Analytics tools can be used to collect statistics about customer interactions and improve system performance.

A customer guarantee should provide outstanding customer support that will build a loyal customer base in the future and create positive feedback that will enhance your brand image and attract new customers. It is possible to turn your conversational AI product into a profitable business. However, it's important to remember that the AI landscape is constantly changing, so it's important to stay on top of current trends and technologies to stay competitive.

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