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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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U.S. lifts chip software curbs on China amid trade truce, Synopsys says

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U.S. lifts chip software curbs on China amid trade truce, Synopsys says

Synopsys logo is seen displayed on a smartphone with the flag of China in the background.

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The U.S. government has rescinded its export restrictions on chip design software to China, U.S.-based Synopsys announced Thursday. 

“Synopsys is working to restore access to the recently restricted products in China,” it said in a statement

The U.S. had reportedly told several chip design software companies, including Synopsys, in May that they were required to obtain licenses before exporting goods, such as software and chemicals for semiconductors, to China. 

The U.S. Commerce Department did not immediately respond to a request for comment from CNBC.

The news comes after China signaled last week that they are making progress on a trade truce with the U.S. and confirmed conditional agreements to resume some exchanges of rare earths and advanced technology.

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Datadog stock jumps 10% on tech company’s inclusion in S&P 500 index

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Datadog stock jumps 10% on tech company’s inclusion in S&P 500 index

The Datadog stand is being displayed on day one of the AWS Summit Seoul 2024 at the COEX Convention and Exhibition Center in Seoul, South Korea, on May 16, 2024.

Chris Jung | Nurphoto | Getty Images

Datadog shares were up 10% in extended trading on Wednesday after S&P Global said the monitoring software provider will replace Juniper Networks in the S&P 500 U.S. stock index.

S&P Global is making the change effective before the beginning of trading on July 9, according to a statement.

Computer server maker Hewlett Packard Enterprise, also a constituent of the index, said earlier on Wednesday that it had completed its acquisition of Juniper, which makes data center networking hardware. HPE disclosed in a filing that it paid $13.4 billion to Juniper shareholders.

Over the weekend, the two companies reached a settlement with the U.S. Justice Department, which had sued in opposition to the deal. As part of the settlement, HPE agreed to divest its global Instant On campus and branch business.

While tech already makes up an outsized portion of the S&P 500, the index has has been continuously lifting its exposure as the industry expands into more areas of society.

DoorDash was the latest tech company to join during the last rebalancing in March. Cloud software vendor Workday was added in December, and that was preceded earlier in 2024 with the additions of Palantir, Dell, CrowdStrike, GoDaddy and Super Micro Computer.

Stocks often rally when they’re added to a major index, as fund managers need to rebalance their portfolios to reflect the changes.

New York-based Datadog went public in 2019. The company generated $24.6 million in net income on $761.6 million in revenue in the first quarter of 2025, according to a statement. Competitors include Cisco, which bought Splunk last year, as well as Elastic and cloud infrastructure providers such as Amazon and Microsoft.

Datadog has underperformed the broader tech sector so far this year. The stock was down 5.5% as of Wednesday’s close, while the Nasdaq was up 5.6%. Still, with a market cap of $46.6 billion, Datadog’s valuation is significantly higher than the median for that index.

— CNBC’s Ari Levy contributed to this report.

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Datadog CEO Olivier Pomel on the cloud computing outlook

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Ether and related stocks gain amid the latest crypto craze: Tokenization

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Ether and related stocks gain amid the latest crypto craze: Tokenization

A representation of cryptocurrency Ethereum is placed on a PC motherboard in this illustration taken on June 16, 2023.

Dado Ruvic | Reuters

Stocks tied to the price of ether, better known as ETH, were higher on Wednesday, reflecting renewed enthusiasm for the crypto asset amid a surge of interest in stablecoins and tokenization.

BitMine Immersion Technologies, a bitcoin miner that announced plans this week to make ETH its primary treasury reserve asset, jumped about 20%. It’s gained more than 1,000% since the announcement. Betting platform SharpLink Gaming, which has also initiated an ETH treasury strategy, added more than 11%. Bit Digital, which last week exited bitcoin mining to focus on its ETH treasury and staking plans, jumped more than 6%.

“We’re finally at the point where real use cases are emerging, and stablecoins have been the first version of that at scale but they’re going to open the door to a much bigger story around tokenizing other assets and using digital assets in new ways,” Devin Ryan, head of financial technology research at Citizens.

On Tuesday, as bitcoin ETFs snapped a 15-day streak of inflows, ether ETFs saw $40 million in inflows led by BlackRock’s iShares Ethereum Trust. ETH ETFs came back to life in June after much concern that they were becoming zombie funds.

The price of the coin itself was last higher by 5%, according to Coin Metrics, though it’s still down 24% this year.

Ethereum has been struggling with an identity crisis fueled by uncertainty about the network’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.

The Ethereum network’s smart contracts capability makes it a prominent platform for the tokenization of traditional assets, which includes U.S. dollar-pegged stablecoins. Fundstrat’s Tom Lee this week called Ethereum “the backbone and architecture” of stablecoins. Both Tether (USDT) and Circle‘s USD Coin (USDC) are issued on the network.

Fundstrat's Tom Lee on being named chairman of BitMine Immersion Technologies

BlackRock’s tokenized money market fund (known as BUIDL, which stands for USD Institutional Digital Liquidity Fund) also launched on Ethereum last year before expanding to other blockchain networks.

Tokenization is the process of issuing digital representations on a blockchain network of publicly traded securities, real world assets or any other form of value. Holders of tokenized assets don’t have outright ownership of the assets themselves.

The latest wave of interest in ETH-related assets follows an announcement by Robinhood this week that it will enable trading of tokenized U.S. stocks and ETFs across Europe, after a groundswell of interest in stablecoins throughout June following Circle’s IPO and the Senate passage of its proposed stablecoin bill, the GENIUS Act.

Ether, which turns 10 years old at the end of July, is sitting about 75% off its all-time high.

Don’t miss these cryptocurrency insights from CNBC Pro:

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