Connect with us

Published

on

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. 

related investing news

Nvidia's 'iPhone moment' in AI signals tons of future growth. Here's our new price target

CNBC Investing Club

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.” 


Subscribe to CNBC on YouTube. 

Continue Reading

Technology

Meta approached Perplexity before massive Scale AI deal

Published

on

By

Meta approached Perplexity before massive Scale AI deal

Meta approached Perplexity before massive Scale AI deal

Meta approached artificial intelligence startup Perplexity AI about a potential takeover bid before ultimately investing $14.3 billion into Scale AI, CNBC confirmed on Friday.

The two companies did not finalize a deal, according to two people familiar with the matter who asked not to be named because of the confidential nature of the negotiations.

One person familiar with the talks said it was “mutually dissolved,” while another person familiar with the matter said Perplexity walked away from a potential deal.

Bloomberg earlier reported the talks between Meta and Perplexity. Perplexity declined to comment. Meta did not immediately respond to CNBC’s request for comment.

Meta’s attempt to purchase Perplexity serves as the latest example of Mark Zuckerberg‘s aggressive push to bolster his company’s AI efforts amid fierce competition from OpenAI and Google parent Alphabet. Zuckerberg has grown agitated that rivals like OpenAI appear to be ahead in both underlying AI models and consumer-facing apps, and he is going to extreme lengths to hire top AI talent, as CNBC has previously reported.

Read more CNBC reporting on AI

Meta now has a 49% stake in Scale after its multibillion-dollar investment, though the social media company will not have any voting power. Scale AI’s founder Alexandr Wang, along with a small number of other Scale employees, will join Meta as part of the agreement.

Earlier this year, Meta also tried to acquire Safe Superintelligence, which was reportedly valued at $32 billion in a fundraising round in April, as CNBC reported on Thursday.

Daniel Gross, the CEO of Safe Superintelligence, and former GitHub CEO Nat Friedman are joining Meta’s AI efforts, where they will work on products under Wang. Gross runs a venture capital firm with Friedman called NFDG, their combined initials, and Meta will get a stake in the firm.

OpenAI CEO Sam Altman said on the latest episode of the “Uncapped” podcast, which is hosted by his brother, that Meta had tried to poach OpenAI employees by offering signing bonuses as high as $100 million with even larger annual compensation packages.

“I’ve heard that Meta thinks of us as their biggest competitor,” Altman said on the podcast. “Their current AI efforts have not worked as well as they have hoped and I respect being aggressive and continuing to try new things.”

–CNBC’s Kate Rooney contributed to this report

WATCH: Meta tried to buy Perplexity before Scale AI deal

Continue Reading

Technology

Why ether ETF inflows have come roaring back from the dead

Published

on

By

Why ether ETF inflows have come roaring back from the dead

Omar Marques | Lightrocket | Getty Images

Ether ETFs have finally come to life this year after some started to fear they may be becoming zombie funds.

Collectively, the funds tracking the price of spot ether are on pace for their sixth consecutive week of inflows and eight positive week in the last nine, according to SoSoValue.

The second largest cryptocurrency has become more attractive to institutions in recent weeks largely due to recent regulatory momentum in the U.S. around stablecoins – many of which run on the Ethereum network – the successful IPO of Circle, the issuer of the second-largest stablecoin; and new leadership at the Ethereum Foundation.

“What we’re seeing is institutional recalibration,” said Ben Kurland, CEO at crypto charting and research platform DYOR. “After the initial ETH ETF approval fizzled without a price pop, smart money started quietly building positions. They’re betting not on price momentum but on positioning ahead of utility unlocks like staking access, options listings, and eventually inflows from retirement platforms.”

The first year of ether ETFs, which launched in July 2024, has been characterized by weak demand. While the funds have had spikes in inflows, they’ve trailed far behind bitcoin ETFs in both inflows and investor attention – amassing about $3.9 billion in net inflows since listing versus bitcoin ETFs’ $36 billion in their first year of trading.

“With increasing acceptance of crypto on Wall Street, especially now as a means for payments and remittances, investors are being drawn to ETH ETFs,” said Chris Rhine, head of liquid active strategies at Galaxy Digital.

Additionally, he added, the CME basis on ether – or the price difference between ether futures and the spot price – is higher than that of bitcoin, giving arbitrageurs an opportunity to profit by going long on ether ETFs while shorting futures (a common trading strategy) and contributing to the uptrend in ether ETF inflows.

Stock Chart IconStock chart icon

hide content

Ether (ETH) 1 month

Despite the uptrend in inflows, the price of ether itself is negative for this month and flat over the past month.

For the year, it’s down 25% as it’s been suffering from an identity crisis fueled by uncertainty about Ethereum’s value proposition, weaker revenue since its last big technical upgrade and increasing competition from Solana. Market volatility driven by geopolitical uncertainty this year has not helped.

In March, Standard Chartered slashed its ether price target by more than half. However, the firm also said the coin could still see a turnaround this year.

Since last week’s big spike in inflows, they’ve “slowed but stayed net positive, suggesting conviction, not hype,” Kurland said. “The market looks like a heart monitor, but the buyers are treating it like a long-term infrastructure bet.”

Don’t miss these cryptocurrency insights from CNBC Pro:

Continue Reading

Technology

Chip stocks fall on report U.S. could terminate waivers for Taiwan Semi and others

Published

on

By

Chip stocks fall on report U.S. could terminate waivers for Taiwan Semi and others

A motorcycle is seen near a building of the Taiwan Semiconductor Manufacturing Company (TSMC), which is a Taiwanese multinational semiconductor contract manufacturing and design company, in Hsinchu, Taiwan, on April 16, 2025.

Daniel Ceng | Anadolu | Getty Images

Semiconductor stocks declined Friday following a report that the U.S. is weighing measures that would terminate waivers allowing some chipmakers to send American technology to China.

Commerce Department official Jeffrey Kessler told Samsung Electronics, SK Hynix and Taiwan Semiconductor this week that he wanted to cancel their waivers, which allow them to send U.S. chipmaking tech to their factories in China, the Wall Street Journal reported, citing people familiar with the matter.

The VanEck Semiconductor ETF declined about 1%. Nvidia, Qualcomm and Marvell Technology fell about 1%, while Taiwan Semiconductor slipped about 2%.

The latest reported move by the Commerce Department comes as the U.S. and China hold an unsteady truce over tariffs and trade, with chip controls a key sticking point.

Read more CNBC tech news

The countries agreed to the framework of a second trade agreement in London days ago after relations soured following the initial tariff pause in May.

The U.S. issued several chip export changes after the May pause that rattled relations, with China calling the rules “discriminatory.”

U.S. chipmakers have been hit with curbs over the last few years, limiting the ability to sell advanced artificial intelligence chips to China due to national security concerns.

During its earnings report last month, Nvidia said the recent export restriction on its China-bound H20 chips hindered sales by about $8 billion.

Nvidia CEO Jensen Huang told investors on an earnings call that the $50 billion market in China for AI chips is “effectively closed to U.S. industry.” During a CNBC interview in May, he called getting blocked from China’s AI market a “tremendous loss.”

Read the full WSJ report here.

WATCH: U.S. prepares action targeting allies’ ability to ship American chip-making equipment to China

U.S. prepares action targeting allies' ability to ship American chip-making equipment to China

Continue Reading

Trending