What Is Google Gemini (Formerly Bard) AI Model? | Definition from TechTarget

AI Is Coming? No, It's Already Here.

AI is coming? No, it's already here.

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2023 will go down as the year when Artificial Intelligence (AI) became omnipresent in the lexicon of society. Companies at the forefront of the AI revolution dominated the headlines and outperformed the broader market. In Q4 2023 earnings calls, 36% of S&P 500 companies mentioned "AI", up from 31% in Q3. That trend is likely to accelerate during upcoming Q1 2024 earnings calls, considering that companies mentioning AI during Q4 2023 posted an average stock price increase of over 28% last year.

For investors, the challenge in navigating the AI euphoria lies in separating the hype from the reality, and there are potential gains to be had for those who can think outside the box and identify overlooked areas where AI technology can be applied. But what exactly is AI, and can it deliver on promises and hype?

For most people, the term evokes thoughts of science fiction movies in which computers or robots achieve a degree of sentience, reaching or even exceeding human intelligence (and frequently going rouge, à la 2001's HAL or The Matrix's Agent Smith). The reality is that AI in its present state is more akin to an open-ended computer program. AI mimics human learning in identifying patterns, making predictions, and analyzing results and applying prior successes and failures towards constant improvement.

AI is already here, and you already interact with it, possibly without even realizing it. The predictive text on your smartphone (and Microsoft MSFT Word, which finished that sentence as it was being typed) is a form of AI. The (possibly frustrating) customer service agent you chatted with on an e-commerce website was possibly AI and if not, it soon will be. Did you unlock your phone by using facial recognition? That was AI again. There are countless other examples, such as the movies that Netflix NFLX (NFLX) suggests, the stories and posts on your Facebook (META) feed, and the traffic alerts that show up in Google (GOOG) Maps.

These relatively mundane, everyday use cases are often overlooked amidst the excitement over more futuristic sounding promises of automated vehicles, robotic factory workers, and neural implants that could increase human brainpower. While we are rapidly progressing towards those three examples, the next stage in AI is likely a widespread adoption beyond traditional tech companies by other industries.

One of the most obvious and exciting applications for AI is the potential to accelerate scientific and medical research. AI can potentially speed up pharmaceutical development and testing, by identifying optimal chemical compounds and making predictions on the efficacy of drugs in development. AI can assist in cataloguing and drawing conclusions over drug performance and side effects and possibly identify potential adverse effects in advance – drugmakers such as Pfizer PFE (PFE) have used AI in this capacity for roughly a decade already.

Outside the healthcare sector, retailers of all types are beginning to apply AI to analyze customer behavior, processing massive amounts of real-time data on buying patterns, finding optimal pricing, and managing inventory. Much to the chagrin of music and sports fans, ticket-sellers such as Ticketmaster (TKTM) and StubHub have implemented AI to apply dynamic or "surge" pricing algorithms that automatically raise prices to coincide with peak demand.

As AI continues to improve and evolve, humans will no longer be required for several jobs, and the technology will augment human workers in even more roles. Customer service, data entry, and telemarketing roles are already being replaced and AI can also be trained to handle less-complex computer programming and coding tasks. Presently, machines are responsible for 34% of business tasks, but that percentage is expected to grow to 43% by 2027 according to a World Economic Forum study. Thankfully, at least a portion of the job losses will be offset by the need for more data scientists, engineers, robotics experts, and other highly skilled roles.

As investors, there are several ways to position portfolios for the coming AI revolution. The simplest would be to stay the course and maintain market-cap weighted exposure to the US economy. The US is at the forefront of the AI revolution and the technology will permeate through all economic sectors as already mentioned. The successful companies will see the biggest share price gains and therefore hold larger weight in the market-cap indices (as has been the case for Nvidia, which has grown from $200 Billion to over $2.2 Trillion in just 5 years). In 2023 we saw this play out, as the "Magnificent Seven" mega-cap stocks – all of which have significant AI exposure – accounted for a disproportionate amount of the S&P 500's return.

For investors looking to be more aggressive, allocating more heavily to the Nasdaq or the S&P Technology Sector ETF (XLK XLK ) is a way to increase AI exposure. While Tech won't be the exclusive beneficiary of the AI boom, the chipmakers and cloud data storage operators are essentially the nuts-and-bolts of AI and still have plenty of runway despite their incredible recent performance. There are also specialized ETFs available focusing on AI, such as the Invesco AI and Next Gen Software ETF (IGPT), or the Global X Robotics and AI ETF (BOTZ BOTZ ).

To position portfolios for the "second wave" AI boom, in which non-tech companies integrate and apply AI technology to improve margins and accelerate growth, investors should look to identify companies that are financially healthy to engage in cap-ex spending. With interest rates still elevated, companies with healthy cash flows and a track record of spending on R&D will obtain a first mover advantage on building out their AI strategies. Screening the Large Cap universe of stocks for those with highest ratio of R&D spending to Revenue yields non-tech companies such as Deere (DE), Johnson & Johnson JNJ (JNJ), and Schlumberger SLB (SLB). Expanding the search into Small- and Mid-Caps reveals companies such as medical device maker Edward Lifesciences (EW), chemical maker FMC FMC Corp (FMC), and glassmaker Corning GLW (GLW). Even newspaper publisher the New York Times NYT (NYT), which sued Microsoft and OpenAI over ChatGPT's tendency to plagiarize its content, recently announced plans to hire AI-specialized staff. While there is no guarantee that these companies will successfully integrate AI into their respective businesses, identifying firms willing to spend on R&D may be a way to find the next, less-obvious beneficiaries of the AI revolution.

AI is looking less like a dot-com bubble 2.0 and more like a revolutionary breakthrough that will unlock efficiency and alter the way companies do business in years to come. AI is already spreading beyond the technology sector and in a few short years, will likely be a universally necessary strategic initiative across all major industries. Investors can capitalize on the AI boom by looking beyond the obvious beneficiaries and positioning their portfolios on the crest of the "second wave".

How The Generative AI Backlash Took Over The Internet

The backlash against Generative AI is growing

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AI-generated media — images, music, writing and video — has steadily spread through the web, and the internet is becoming stranger by the day.

The Dead Internet Theory is manifesting into reality and conspiracy theories are thriving, boosted by the rise of deepfake imagery and video.

The AI hype cycle has reached an interesting new stage, where investors are pouring money into the technology, but negative stories are dominating the discourse — the Taylor Swift deepfake scandal, the Glasgow Willy Wonka fiasco, the backlash against AI-generated assets used in Late Night With the Devil and Doctor Who, and numerous copyright lawsuits.

Billy Coul, the organizer behind the Glasgow Willy Wonka fiasco, has been named and shamed by Rolling Stone as a "corner-cutting huckster," who used generative AI to publish sixteen books on Amazon.

Coul has since been dubbed "Willy Wanker" by the internet, but he is far from alone in using generative AI to try and make a quick buck.

The technology has emboldened scammers who are flooding online marketplaces with AI-generated imagery and writing; meaningless content with no creator, polluting the waters of the world wide web.

Much of AI-generated art appears lifeless and uncanny, littered with unsettling "hallucinations" — twisted fingers and misshapen furniture, crowds with distorted faces.

Recent reports show that public trust in AI is in steep decline, a shift highlighted by a clip from the SXSW festival that went viral, showing the crowd booing in response to a sizzle reel of tech leaders endorsing the wonders of generative AI.

The initial promise of generative AI, that it would lead to greater creative freedom, has been eclipsed by the bitter reality; the technology is being used to cut costs and replace workers.

Among the AI-generated tsunami of curvy anime girls and hazy fantasy art, there are artists who are experimenting with AI as a tool, and some have managed to create visually striking and thoughtful work.

However, many artists have spoken out against the technology, pointing out that the creative process, as messy as it is, is not an inconvenient obstacle.

The vast majority of creatives do not want a machine to pump out content on their behalf — art is made by people — it isn't ordered at the touch of a button by an impatient consumer, like fast food.

Self-expression takes time and effort, and the story behind the creation of art is often just as interesting as the final piece, and integral to the discussion around it. Creating art is a form of self-expression, not a burden.

How can AI-generated art, inherently devoid of meaning, perspective and intent, have any value beyond novelty?

Does the average consumer really want a landscape filled with media that no one bothered to make?

Outside of philosophical arguments, many artists argue that generative AI models have been "trained" on their work without their consent, and the models are already being used to cut corners in the creative industries.

Many artists were in an unstable, precarious position before the advent of this technology, and they don't stand to gain from its rise.

The threat of generative AI isn't limited to the creative arts; a recent report from the Institute for Public Policy Research estimates that 8 million jobs in the UK could be lost to generative AI in the next five years.

Assuming that the output of AI models will be dynamic, reliable, and cost-effective enough to replace human workers, the public is unlikely to cheer on the arrival of the so-called "jobs apocalypse."

Tech leaders in Silicon Valley consistently promise that AI will eventually outperform all expectations; some even believe that the technology will grow so advanced that it will become sentient.

Today's generative models have no pathway to sentience, or even understanding. But people love to anthropomorphize machines, especially people who head generative AI companies.

Open AI CEO Sam Altman speculated in an 2023 article that a sentient AI, known as AGI (artificial general intelligence), isn't just possible, but inevitable.

Altman wrote: "Because the upside of AGI is so great, we do not believe it is possible or desirable for society to stop its development forever."

Despite Altman's insistence, AGI remains the stuff of science fiction.

"Hallucinations" have still not been solved, and today's models guzzle water and energy at a terrifying rate, to the point where Altman believes that an AI-powered world will require a "breakthrough" in nuclear fusion.

All that water, energy, infrastructure, all those online scams and spambots, serve to maintain technology that threatens the livelihood of workers and erode the creative industries.

The backlash against generative AI isn't going away, and in the long run, AI might just be viewed as another Silicon Valley fad, like NFTs, that couldn't possibly live up to the hype.

Here's The AI Company Amazon's Betting Billions On

Earlier this week, Amazon said it'd commit a further $2.75 billion to the San Francisco-based company as part of its efforts to get ahead of other Big Tech competitors in the AI arms race. It's the e-commerce giant's latest investment into the maker of Claude, a generative AI chatbot that rivals OpenAI's ChatGPT, after pouring $1.25 billion into Anthropic last September.

Amazon had said it'd invest up to $4 billion in Anthropic; this latest outlay brings it to the full amount, showing it's all in on the startup.

The transaction includes a previously announced minority ownership stake. Anthropic also said it will use Amazon Web Service's cloud servers and chips to train and power its large language models, allowing them to produce desirable human-like outputs.

So, what's the deal behind the company Amazon is betting billions on?

Anthropic was founded in 2021 by siblings Dario Amodei and Daniela Amodei, CEO and president of the firm, respectively, after they left their jobs at now-competitor OpenAI to focus on building what they describe as safe AI.

Its mission: "to ensure transformative AI helps people and society flourish," according to the company's website.

During its early days, Anthropic focused on research, training, and testing efforts to ensure its AI model acted in a way that aligned with human values. Then, in March 2023, Anthropic launched the inaugural version of Claude, which could do things like summarize text, write code, and answer questions in a human-like way.

And while OpenAI's ChatGPT came out months before Claude did, Anthropic claimed at the time that Claude was "much less likely to product harmful outputs, easier to converse with, and more steerable." However, some critics said its more cautious approach to an AI chatbot makes its outputs less interesting.

"I would certainly rather Claude be boring than that Claude be dangerous," CEO Amodei told the New York Times last July.

Since the initial launch, Anthropic has released a slate of new AI models. The company announced the Claude 3 family in March this year. That includes Haiku, Sonnet, and Opus, models the startup says produce more accurate outputs and perform more complex tasks than their predecessors.

As of March 28th, Opus, which Anthropic claims is its most intelligent model, appears to perform better than GPT-4, the LLM behind ChatGPT, according to Hugging Face's chatbot arena board, which AI researchers use to gauge the computing systems' capabilities.

Other big players in the tech community have also invested in the company. Anthropic has raised about $9.3 billion as of March 27 — the date of Amazon's further investment announcement — according to PitchBook data. In February, before Amazon's latest cash influx, the company's valuation stood at $15 billion, the NYT reported.

Google pledged to invest up to $2 billion in 2023, and crypto trading platform FTX, under Sam Bankman-Fried's leadership, invested $500 million (though the now-bankrupt FTX is selling a majority of the stake for $884 million to a suite of buyers, CNBC reported earlier this week.)

Moving forward, Anthropic plans to release more updates to its Claude 3 model family and make its AI more suitable for companies.

"We do not believe that model intelligence is anywhere near its limits," Anthropic says.

"Generative AI is poised to be the most transformational technology of our time, and we believe our strategic collaboration with Anthropic will further improve our customers' experiences, and look forward to what's next," Swami Sivasubramanian, vice president of Data and AI at AWS, said in an Amazon press release.

Anthropic didn't immediately respond to a request for comment from Business Insider before publication.

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