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As the generative AI field heats up, consumer-facing chatbots are fielding questions about business strategy, designing study guides for math class, offering advice on salary negotiation and even writing wedding vows. And things are just getting started. 

OpenAI’s ChatGPT, Google’s Bard, Microsoft’s Bing and Anthropic’s Claude are a few of today’s leading chatbots, but over the coming year, we’ll likely see more emerge: In the venture capital space, generative AI-related deals totaled $1.69 billion worldwide in Q1 of this year, a 130% spike from last quarter’s $0.73 billion – with another $10.68 billion worth of deals being announced but not yet completed in Q1, according to Pitchbook data. 

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Two months after ChatGPT’s launch, it surpassed 100 million monthly active users, breaking records for the fastest-growing consumer application in history: “a phenomenal uptake – we’ve frankly never seen anything like it, and interest has grown ever since,” Brian Burke, a research VP at Gartner, told CNBC. “From its release on November 30 to now, our inquiry volume has shot up like a hockey stick; every client wants to know about generative AI and ChatGPT.” 

These types of chatbots are built atop large language models, or LLMs, a machine learning tool that uses large amounts of internet data to recognize patterns and generate human-sounding language. If you’re a beginner, many of the sources we spoke with agreed that the best way to start using a chatbot is to dive in and try things out. 

“People spend too much time trying to find the perfect prompt – 80% of it is just using it interactively,” Ethan Mollick, an associate professor at the Wharton School of the University of Pennsylvania, who studies the effects of AI on work and education, told CNBC. 

Here are some tips from the pros:

Keep data privacy in mind. 

When you use a chatbot like ChatGPT or Bard, the information you put in – what you type, what you receive in response, and the changes you ask for – may be used to train future models. OpenAI says as much in its terms. Although some companies offer ways to opt out – OpenAI allows this under “data controls” in ChatGPT settings – it’s still best to refrain from sharing sensitive or private data in chatbot conversations, especially while companies are still finessing their privacy measures. For instance, a ChatGPT bug in March briefly allowed users to see parts of each others’ conversation histories. 

“If you wouldn’t post it on Facebook, don’t put it into ChatGPT,” Burke said. “Think about what you put into ChatGPT as being public information.”

Offer up context. 

For the best possible return on your time, give the chatbot context about how it should act in this scenario, and who it’s serving with this information. For example, you can write out the persona you want the chatbot to assume in this scenario: “You are a [marketer, teacher, philosopher, etc.].” You can also add context like: “I am a [client, student, beginner, etc.].” This could save time by directly telling the chatbot which kind of role it should assume, and which “lens” to pass the information through in a way that’s helpful to you. 

For instance, if you’re a creative consultant looking for a chatbot to help you with analysis on company logos, you could type out something like, “Act as if you are a graphic designer who studies logo design for companies. I am a client who owns a company and is looking to learn about which logos work best and why. Generate an analysis on the ‘best’ company logos for publicly listed companies and why they’re seen as good choices.” 

“If you ask Bard to write an inspirational speech, Bard’s response may be a bit more generic – but if you ask Bard to write a speech in a specific style, tone or format, you’ll likely get a much better response,” Sissie Hsiao, a VP at Google, told CNBC.

Make the chatbot do all the work.

Sometimes the best way to get what you want is to ask the chatbot itself for advice – whether you’re asking about what’s possible as a user, or about the best way to word your prompt.

“Ask it the simple question, what kinds of things can you do? And it’ll give you a list of things that would actually surprise most people,” Burke said. 

You can also game the system by asking something like, “What’s the best way to ask you for help writing a shopping list?” or even assigning the chatbot a prompt-writing job, like, “Your job is to generate the best and most efficient prompts for ChatGPT. Generate a list of the best prompts to ask ChatGPT for healthy one-pot dinner recipes.” 

Ask for help with brainstorming. 

Whether you’re looking for vacation destinations, date ideas, poetry prompts or content strategies for going viral on social media, many people are using chatbots as a jumping-off point for brainstorming sessions. 

“The biggest thing…that I find them to be helpful for is inspiring me as the user and helping me learn things that I wouldn’t have necessarily thought of on my own,” Josh Albrecht, CTO of Generally Intelligent, an AI research startup, told CNBC. “Maybe that’s why they’re called generative AI – they’re really helpful at the generative part, the brainstorming.” 

Create a crash course. 

Let’s say you’re trying to learn about geometry, and you consider yourself a beginner. You could kick off your studies by asking a chatbot something like, “Explain the basics of geometry as if I’m a beginner,” or, “Explain the Pythagorean Theorem as if I’m a five-year-old.” 

If you’re looking for something more expansive, you can ask a chatbot to create a “crash course” for you, specifying how much time you’ve got (three days, a week, a month) or how many hours you want to spend learning the new skill. You can write something like, “I’m a beginner who wants to learn how to skateboard. Create a two-week plan for how I can learn to skateboard and do a kickflip.” 

To expand your learning plan beyond the chatbot, you can also ask for a list of the most important books about a topic, some of the most influential people in the field and any other resources that could help you advance your skill set. 

Don’t be afraid to give notes and ask for changes. 

“The worst thing you could do if you’re actually trying to use the output of ChatGPT is [to] just ask it one thing once and then walk away,” Mollick said. “You’re going to get very generic output. You have to interact with it.”

Sometimes you won’t choose the perfect prompt, or the chatbot won’t generate the output you were looking for – and that’s okay. You can still make tweaks to make the information more helpful, like asking follow-up questions like, “Can you make it sound less generic?” or “Can you make the first paragraph more interesting?” or even restating your original ask in a different way. 

Take everything with many grains of salt.

Chatbots have a documented tendency to fabricate information, especially when their training data doesn’t fully cover an area you’re asking about, so it’s important to take everything with a grain of salt. Say you’re asking for a biography of Albert Einstein: A chatbot might tell you the famous scientist wrote a book called “How to Be Smart,” when, unfortunately, he never did. Also, since large language models are trained upon large swaths of the internet, they’re best at pattern recognition, meaning they can generate biased outputs or misinformation based on their training data. 

“Where there’s less information, it just makes stuff up,” Burke said, adding, “These hallucinations are extraordinarily convincing…You can’t trust these models to give you accurate information all the time.”

Experiment and try different approaches.

Whether you’re asking for a chatbot to generate a list of action items from a meeting transcript or translate something from English to Tagalog, there are an untold range of use cases for generative AI. So when you’re using a chatbot, it’s worth thinking about the things you want to learn or need help with and experimenting with how well the system can deliver. 

“AI is a general-purpose technology; it does a lot of stuff, so the idea is that whatever field you’re in and whatever job you’re in, it’s going to affect aspects of your job differently than anyone else on the planet,” Mollick said. “It’s about thinking about how you want to use it…You have to figure out a way to work with the system…and the only way to do that is through experimenting.” 


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Meta shares plunge on weak revenue guidance even as first-quarter results top estimates

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Meta shares plunge on weak revenue guidance even as first-quarter results top estimates

Meta shares plunged more than 11% in extended trading on Wednesday after the company issued a light forecast, which overshadowed better-than-expected first-quarter results.

Here are the key numbers:

  • Earnings per share: $4.71 per share vs. $4.32 per share expected by LSEG
  • Revenue: $36.46 billion vs. $36.16 billion expected by LSEG

Revenue increased 27% from $28.65 billion in the same period a year earlier, the fastest rate of expansion for any quarter since 2021. Net income more than doubled to $12.37 billion, or $4.71 per share, from $5.71 billion, or $2.20 per share, a year ago.

One reason for the pop in net income is that, while revenue growth accelerated, sales and marketing costs dropped 16% in the quarter from a year earlier.

Meta said it expects sales in the second quarter of $36.5 billion to $39 billion. The midpoint of the range, $37.75 billion, would represent 18% year-over-year growth and is below analysts’ average estimate of $38.3 billion.

The company no longer reports daily active users and monthly active users. It now gives a figure for what it calls “family daily active people.” That number was 3.24 billion for March 2024, a 7% increase from a year earlier.

Meta has raised investor expectations due to its improved financial performance in recent quarters, leaving little room for error. The stock is up about 40% this year after almost tripling last year. In February 2023, CEO Mark Zuckerberg told investors it would be the “year of efficiency,” which initiated the rally.

At the time, Zuckerberg said the company would be better at eliminating unnecessary projects and cracking down on bloat, which would help Meta become a “stronger and more nimble organization.” The company cut about 21,000 jobs in the first half of 2023, and Zuckerberg said in February of this year that hiring will be “relatively minimal compared to what we would have done historically.”

Headcount declined by 10% in the first quarter from a year earlier to 69,329.

Capital expenditures for 2024 will be $35 billion to $40 billion, an increase from a prior forecast of $30 billion to $37 billion “as we continue to accelerate our infrastructure investments to support our artificial intelligence (AI) roadmap,” Meta said.

Average revenue per user in the quarter was $11.20, Meta said.

The Facebook parent has been clawing back digital ad market share after a dismal 2022. At that time, the company was reeling from Apple’s iOS privacy update and macroeconomic concerns that led many brands to rein in spending.

Zuckerberg spearheaded an initiative to rebuild the ad business with a focus on AI. On the company’s last earnings call in February, finance chief Susan Li said Meta has been investing in AI models that can accurately predict relevant ads for users, as well as tools that automate the ads-creation process. 

Advertising revenue, which accounts for the vast majority of Meta’s business, jumped 27% to $35.64 billion.

Meta is benefiting from a stabilizing economy and surge in spending from Chinese discount retailers like Temu and Shein, which have been pumping money into Facebook and Instagram in an effort to reach a wider swath of users. Some analysts have warned that slower spending from China-based advertisers could be a source of concern in the first quarter and as the year progresses.

The company’s Reality Labs unit, which houses the company’s hardware and software for development of the nascent metaverse, continues to bleed cash. Reality Labs reported sales of $440 million for the quarter and $3.85 billion in losses, bringing total losses since the end of 2020 to over $45 billion.

Analysts expected the division to show an operating loss of $4.31 billion for the quarter.

Executives will discuss the company’s results on a call with analysts at 5 p.m. ET.

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Meta’s Reality Labs posts $3.85 billion loss in first quarter

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Meta's Reality Labs posts .85 billion loss in first quarter

Facebook co-founder and chief executive, Mark Zuckerberg, speaks at an Oculus developers conference while wearing a virtual reality headset in San Jose, California.

Glen Chapman | AFP | Getty Images

Meta shows no signs of substantially trimming its losses from investing in the metaverse, as competition heightens between the Facebook parent and Apple in the virtual reality market.

In its first-quarter earnings report Wednesday, Meta disclosed that its Reality Labs unit recorded a $3.85 billion operating loss. Revenue in the metaverse division was $440 million, up about 30% from $339 million a year ago and representing only around 1% of Meta’s total sales for the quarter.

Analysts were expecting a $4.31 billion operating loss and sales of $512.5 million for the quarter, according to StreetAccount.

Reality Labs has now lost more than $45 billion since the end of 2020, when Meta first began reporting the business segment separately.

Meta CEO Mark Zuckerberg has called the metaverse “the next frontier,” imagining a digital world that facilitates both productivity and recreation. He changed the name of his company from Facebook to Meta in 2021 to reflect his vision for the future of computing.

For now, developing metaverse technology remains a fledgling and costly effort.

The company unveiled in September the Quest 3 VR headset, the latest version of its mixed reality hardware, with a starting price of $499. Apple started selling its $3,499 Vision Pro in February, touting a so-called “spatial computing” experience.

Meta announced Monday that it will partner with third-party hardware companies to create new VR headsets using the same Meta Horizon operating system that powers its Quest headsets. Zuckerberg said that while Apple “basically won out” in the phone market with its closed ecosystem, Meta’s move aims to ensure the “open model defines the next generation of computing.”

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IBM to acquire HashiCorp in $6.4 billion deal, reports another revenue miss

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IBM to acquire HashiCorp in .4 billion deal, reports another revenue miss

IBM CEO Arvind Krishna appears at the World Economic Forum in Davos, Switzerland, on Jan. 16, 2024.

Stefan Wermuth | Bloomberg | Getty Images

IBM shares slipped as much as 6% in extended trading on Wednesday after the hardware, software and consulting provider said it would acquire cloud software maker HashiCorp and reported first-quarter revenue that was lower than analysts had predicted.

In a statement, IBM announced that it intends to pay $35 per share in cash for HashiCorp in a deal with a $6.4 billion enterprise value, net of cash. On Tuesday, The Wall Street Journal reported that IBM was getting close to acquiring HashiCorp, sending shares upward. Bloomberg said earlier on Wednesday that IBM was looking to offer $35 per share.

The deal would be accretive to adjusted earnings before interest, taxes, depreciation and amortization in the first full year after close, and accretive to free cash flow in the second year after close. IBM said it expects the transaction to close by the end of 2024. Dave McJannet, HashiCorp’s CEO, will report to Rob Thomas, IBM’s senior vice president in charge of software, if the deal goes through, a spokesperson said.

HashiCorp would complement Red Hat, which has contributed to IBM’s revenue growth since the $34 billion acquisition in 2019. IBM now sells Red Hat’s version of the Linux operating system for use on multiple public clouds, making it a neutral entity. HashiCorp pioneered open-source software that developers rely on to control cloud infrastructure. Premium versions of the Terraform cloud-management software and other products have brought revenue to HashiCorp.

In 2021 HashiCorp shares started trading on the Nasdaq. But revenue growth has slowed, and the company has continued to report losses. Still, it’s adding revenue at a faster pace than IBM.

HashiCorp shares moved 4% higher in extended trading following the acquisition announcement.

Here’s how IBM did in comparison with the consensus among analysts polled by LSEG:

  • Earnings per share: $1.68 adjusted vs. $1.60 expected
  • Revenue: $14.46 billion vs. $14.55 billion expected

IBM’s revenue increased around 1.5% year-over-year during the quarter, according to a statement. This marks the company’s third revenue miss in the last five quarters.

Revenue from software, at $5.90 billion, increased about 6% and was below the $5.96 billion consensus among analysts surveyed by StreetAccount.

IBM’s consulting revenue came in at $5.19 billion, down slightly and just under the $5.20 billion StreetAccount consensus.

Infrastructure revenue totaled $3.08 billion. It declined 0.7% but came in higher than the StreetAccount consensus of $2.94 billion.

During the quarter, IBM said it was providing its 160,000 consultants with artificial intelligence assistants to boost productivity, and the company completed the divestiture of The Weather Company to Francisco Partners.

Notwithstanding the after-hours move, IBM shares are up about 13% so far this year, outperforming the S&P 500 index, which is up 6% over the same period.

Executives will discuss the report with analysts on a conference call starting at 5 p.m. ET.

This is breaking news. Please check back for updates.

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