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Apple CEO Tim Cook stands next to the new Apple Vision Pro headset is displayed during the Apple Worldwide Developers Conference on June 05, 2023 in Cupertino, California.

Justin Sullivan | Getty Images

The last time technology stocks had a better first half, Apple was touting its Lisa desktop computer, IBM was the most-valuable tech company in the U.S. and Mark Zuckerberg hadn’t been born.

On Friday, the Nasdaq wrapped up the first six months of the year with a 1.5% rally, bringing its gains so far for 2023 to 32%. That’s the sharpest first-half jump in the tech-heavy index since 1983, when the Nasdaq rose 37%.

It’s a startling achievement, given what’s happened in the tech industry over the past four decades. Microsoft went public in 1986, sparking a PC software boom. Then came the internet browsers of the 1990s, leading up to the dot-com bubble years and the soaring prices of e-commerce, search and computer-networking stocks. The past decade saw the emergence of the mega-cap, trillion-dollar companies, which are now the most valuable enterprises in the U.S.

While those prior eras featured sustained rallies, none of them had a start to the year rivaling 2023.

Even more stunning, it’s happening this year while the U.S. economy is still at risk of slipping into recession and reckoning with a banking crisis, highlighted by the collapse in March of Silicon Valley Bank, the financial nucleus for much of the venture and startup world. The Federal Reserve also steadily increased its benchmark interest rate to the highest since 2007.

But momentum is always a driver when it comes to tech, and investors are notoriously fearful of missing out, even if they simultaneously worry about frothy valuations.

Coming off a miserable 2022, in which the Nasdaq lost one-third of its value, the big story was cost-cutting and efficiency. Mass layoffs at Alphabet, Meta and Amazon as well as at numerous smaller companies paved the way for a rebound in earnings and a more realistic outlook for growth.

Meta and Tesla, which both got hammered last year, have more than doubled in value so far in 2023. Alphabet is up 36% after dropping 39% in 2022.

None of those companies were around the last time the Nasdaq had a better start to the year. Meta CEO Zuckerberg, who created the company formerly known as Facebook in 2004, was born in 1984. Tesla was founded in 2003, five years after Google, the predecessor to Alphabet.

As 2023 got going, attention turned to artificial intelligence and a flood of activity around generative AI chatbots, which respond to text-based queries with intelligent and conversational responses. Microsoft-backed OpenAI has become a household name (and was No. 1 on CNBC’s Disruptor 50 list) with its ChatGPT program, and dollars are pouring into Nvidia, whose chips are used to power AI workloads at many of the companies taking advantage of the latest advancements.

Nvidia shares soared 190% in the first half, lifting the 30-year-old company’s market cap past $1 trillion.

“I think you’re going to continue to see tech dominate because we’re still all abuzz about AI,” said Bryn Talkington, managing partner at Requisite Capital Management, in an interview with CNBC’s “Closing Bell” on Thursday.

Watch CNBC’s full interview with Requisite's Bryn Talkington and Virtus' Joe Terranova

Talkington, whose firm holds Nvidia shares, said the chipmaker has a unique story, and that its growth is not shared across the industry. Rather, large companies working on AI have to spend heavily on Nvidia’s technology.

“Nvidia not only owns the shovels and axes of this AI goldrush,” Talkington said. “They actually are the only hardware store in town.”

Remember the $10,000 Lisa?

Apple hasn’t seen gains quite so dramatic, but the stock is still up 50% this year, trading at a record and pushing the iPhone maker to a $3 trillion market cap.

Apple still counts on the iPhone for the bulk of its revenue, but its latest jump into virtual reality with the announcement this month of the Vision Pro headset has helped reinvigorate investor enthusiasm. It was Apple’s first major product release since 2014, and will be available starting at $3,499 beginning early next year.

That sounds like a lot, except when compared to the price tag for the initial Lisa computer, which Apple rolled out 40 years ago. That PC, named after co-founder Steve Jobs’ daughter, started at $10,000, keeping it far out of the hands of mainstream consumers.

Apple’s revenue in 1983 was roughly $1 billion, or about the amount of money the company brought in on an average day in the first quarter of 2023 (Apple’s fiscal second quarter).

Tech was the clear story for the equity markets in the first half, as the broader S&P 500 notched a 16% gain and the Dow Jones Industrial Average rose just 2.9%.

Investors looking for red flags heading into the second half don’t have to look far.

Global economic concerns persist, highlighted by uncertainty surrounding the war in Russia and Ukraine and ongoing trade tensions with China. Short-term interest rates are now above 5%, meaning investors can get risk-free returns in the mid-single digits from certificates of deposit and high-yield savings accounts.

Another sign of skepticism is the absence of a tech IPO market, as emerging companies continue to sit on the sidelines despite brewing enthusiasm across the industry. There hasn’t been a notable venture capital-backed tech IPO in the U.S. since late 2021, and investors and bankers tell CNBC that the second half of the year is poised to remain quiet, as companies wait for better predictability in their numbers.

Jim Tierney, chief investment officer of U.S. concentrated growth at AllianceBernstein, told CNBC’s “Power Lunch” on Friday that there are plenty of challenges for investors to consider. Like Talkington, he’s unsure how much of a boost the broader corporate world is seeing from AI at the moment.

“Getting to AI specifically, I think we have to see benefit for all companies,” Tierney said. “That will come, I’m just not sure that’s going to happen in the second half of this year.”

Meanwhile, economic data is mixed. A survey earlier this month from CNBC and Morning Consult found that 92% of Americans are cutting back on spending as inflationary pressures persist.

“The fundamentals get tougher,” Tierney said. “You look at consumer spending today, the consumer is pulling back. All of that suggests that the fundamentals are more stretched here than not.”

WATCH: CNBC’s full interview with Ron Insana and Jim Tierney

Watch CNBC's full interview with Contrast Capital's Ron Insana and Alliance Bernstein's Jim Tierney

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‘Cyber plague’: Experts warn of growing infostealer threat after billions of login details exposed

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'Cyber plague': Experts warn of growing infostealer threat after billions of login details exposed

“Someone, somewhere is having data exfiltrated from their machines as we speak,” says Volodymyr Diachenko, co-founder of the cybersecurity consultancy SecurityDiscovery.

Sarayut Thaneerat | Moment | Getty Images

Cybercriminals have intensified their efforts to steal and sell online passwords, experts warn. The alarm comes after the discovery of online datasets containing billions of exposed account credentials. 

The 30 datasets comprised a whopping 16 billion login credentials across multiple platforms, including Apple, Google and Facebook, and were first reported by Cybernews researchers last week. 

The exposures were identified over the course of this year by Volodymyr Diachenko, co-founder of the cybersecurity consultancy Security Discovery, and are suspected to be the work of multiple parties.

“This is a collection of various data sets that appeared on my radar since the beginning of the year, but they all share a common structure of URLs, login details and passwords,” Diachenko told CNBC. 

According to Daichenko, all signs point to the leaked login information being the work of “infostealers” — malware that extracts sensitive data from devices, including usernames and passwords, credit card information and online browser data. 

While the lists of logins are likely to contain many duplicates as well as outdated and incorrect information, the overwhelming volume of findings puts into perspective how much sensitive data is circulating on the web. 

It should also raise alarms on how infostealers have become the “cyber plague” of today, Daichenko said. “Someone, somewhere, is having data exfiltrated from their machines as we speak.”

Daichenko was able to detect the exposed data because their owners had temporarily indexed them on the web without a password lock. Inadvertently shared data leaks are often caught by Security Discovery, but not at scales seen so far this year.

Infostealer threats on the rise 

According to Simon Green, president of Asia-Pacific and Japan at Palo Alto Networks, the sheer scale of the 16 billion exposed credentials is alarming and certainly notable, but not entirely surprising for those on the front lines of cybersecurity. 

“Many modern infostealers are designed with advanced evasion techniques, allowing them to bypass traditional, signature-based security controls, making them harder to detect and stop,” he added.

Consequently, there’s been an uptick in high-profile infostealer attacks. For example, in March, Microsoft Threat Intelligence disclosed a malicious campaign using infostealers that had affected nearly 1 million devices globally. 

Infostealers typically gain access to victims’ devices by tricking them into downloading the malware, which can be hidden in everything from phishing emails to phony websites to search engine ads.

The motive behind infostealer attacks is usually financial, with attackers often looking to directly take over bank accounts, credit cards, and cryptocurrency wallets or commit identity fraud. 

Cybercriminals can use stolen credentials and other personal data for purposes such as crafting highly convincing, personalized phishing attacks and blackmailing individuals or organizations. 

According to Palo Alto’s Green, the scale and dangers of those types of infostealers have intensified, thanks to the growing prevalence of underground markets that offer “cybercrime-as-a-Service,” in which vendors charge customers for malicious tools, sensitive data and other illicit online services.

“Cyber crime-as-a-Service is the critical enabler here. It has fundamentally democratized cybercrime,” Green said.

Those underground markets — often hosted on the dark web — create demand for cybercriminals to steal personal information and then sell that to scammers. 

In that way, data breaches become about more than just the individual accounts — they represent a “vast, interconnected web of compromised identities” that can fuel subsequent attacks, Green said. 

According to Diachenko, it’s likely that at least some of the compromised login datasets he identified had or will be traded to online scammers. 

On top of that, malware kits and other resources that can help to facilitate infostealer attacks can be found on those markets. 

CNBC has reported on how the availability of those tools and services has significantly lowered technical barriers for aspiring criminals, allowing sophisticated attacks to be executed at a massive, global scale. 

The report found that infostealer attacks grew by 58% in 2024.

What can be done

With the increasing prevalence of malware and online usage, it’s now fair to assume that most people will, at some point, come in contact with an infostealer threat, said Ismael Valenzuela, vice president of threat research and intelligence at cybersecurity company Arctic Wolf.

In addition to frequent password updates, individuals will need to be more alert about the increasing amount of malware hiding in illegitimate software, applications and other downloadable files, Valenzuela said. He added that the use of multi-factor authentication on accounts has become more important than ever.

From a corporate perspective, it’s important to adopt a “zero trust architecture” that not only constantly authenticates the user, but also authenticates the device and user’s behavior, he added.  

Governments have also been doing more to crack down on infostealing activities in recent months.

In May, Europol’s European Cybercrime Centre said it had collaborated with Microsoft and global authorities to disrupt the “Lumma” infostealer, which it called “the world’s most significant infostealer threat.”

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Adopt or die? How Southeast Asian small businesses are using AI to stay competitive

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Adopt or die? How Southeast Asian small businesses are using AI to stay competitive

ASEAN member nations’ flags outside the Pullman Hotel, the venue for the ASEAN Foreign Ministers’ retreat meeting in Luang Prabang, Laos, in January 2024.

Tang Chhin Sothytang Chhin Sothy | Afp | Getty Images

The U.S. and China are usually top of mind when it comes to artificial intelligence and generative AI. But Southeast Asia’s small businesses have huge potential that shouldn’t be ignored, experts say.

In fact, it’s a matter of survival, according to Jochen Wirtz, a professor of marketing at the National University of Singapore Business School, who said those that fall behind will be “moved into a franchise business or will be pushed out of the market by bigger players who do it.”

“Either you grow and adopt, or you die,” he added.

AI and genAI will contribute about $120 billion to the region’s gross domestic product by 2027, Boston Consulting Group projected in an April report titled “Unlocking Southeast Asia’s AI Potential,” which cited the technology’s potential to “redefine business processes and unlock new revenue streams.” And Google’s e-Conomy SEA 2024 report found that Singapore, the Philippines and Malaysia are ranked among the top 10 globally for AI-related searches and demand, indicating “curiosity” and an “active interest” within the region.

Youth is an advantage. Among surveyed countries in the Asia-Pacific, Vietnam, Malaysia and the Philippines have the highest percentage of business owners or leaders under 40 years of age, according to CPA Australia’s Small Business Survey 2024-25.  

For countries such as Vietnam, “the future is bright because … it’s a very young population, is a very internet-savvy population,” said Soumik Parida, associate program manager of the professional communication program at RMIT University Vietnam’s School of Communication and Design. “They are starting to have a global voice and they’re very easy to adapt any new technology,” he added.

Here’s how some of the region’s businesses are using it to stay on top of the competition — as well as the opportunities and roadblocks they face.

Most popular use cases

Customer service is the leading use case in Southeast Asian e-commerce, followed by marketing and advertising, according to a joint report by Lazada and Kantar about AI adoption trends in the six largest economies in Southeast Asia. Also known as the ASEAN-6, they comprise Singapore, Malaysia, Vietnam, Indonesia, the Philippines and Thailand.

A McKinsey survey released in March revealed a similar trend: Companies have adopted genAI for marketing and sales, with tech companies leading the charge. It also showed that most adopters are using the technology to generate text, with 63% of surveyed companies reporting that they do so.

GenAI presents a unique boon for a region as linguistically diverse as Southeast Asia: Aside from writing personalized marketing messages, it can also translate promotional texts into different languages.

For example, Lita Global, an Indonesia-based social media platform for gamers, is benefiting a lot from that. Since integrating OpenAI’s models in the second half of last year, it said, it has been able to host almost twice as many online gaming events monthly, thanks to greater efficiency.

That’s a big boost for its business, since every event can raise weekly revenues by an average of 20%, the company said. 

With genAI, employees can quickly translate announcements about events from English to Southeast Asian languages, such as Vietnamese and Thai, to reach more users in the region. And that frees them up — time originally used for writing, translating and formatting promotional text can now be used for organizing more revenue-generating events, according to Lita Global.

The company also uses genAI in its chat function to recommend responses to users. Lita Global is a social platform where users can hire other gamers to play with them online.

Gamers for hire typically chat with users before an order is placed for a gaming session. But that can be difficult when demand for gamers is high and gamers for hire are busy with other matches. Gamers for hire who use the AI-recommended responses have seen a 10% to 20% uptick in orders, said Lita Global’s CEO Yihao Zhang.

“So we’re using AI to really help them to improve their efficiency, to help them to be more available to the users,” Zhang said.

Another way Southeast Asian MSMEs (micro, small and medium enterprises) can use genAI in marketing is through AI livestreaming. Google’s SEA e-Conomy report noted that live shopping has become more popular in the region. Live shopping, or livestreaming, usually involves a host showcasing the products for sale. Not only does this include clothing try-ons, but shoppers can also ask questions in the comments section, which are answered in real time.

While livestreams are traditionally hosted by humans in studios, MSMEs may lack the funds or technical know-how to execute regular livestreams to boost sales. AI livestreaming can open doors to new opportunities for sellers, said Jensen Wu, CEO of TopviewAI.

TopviewAI says on its website that its AI livestreaming services can cost around $1 per minute. Instead of spending on studio rental, samples of the merchandise and labor of human hosts, companies can have one person monitor the livestream, Wu said. That helps lower costs while boosting sales, making for a “pretty good” return on investment, he added.

The problem of costs

The efficiency boost doesn’t come cheap, however.                             

That’s why small businesses are limited to adopting AI on a small scale for now. Using AI chatbots for relatively simple tasks, for example, can reduce labor costs as subscriptions for such services tend to be inexpensive. On top of that, with a variety of third-party tools available on the market, business owners can also have their pick, according to RMIT Vietnam’s Parida.

Small businesses in the fashion, and food and beverage industries in Vietnam, for example, have begun using chatbots to manage inquiries and orders, Parida said.

“Anything beyond that requires a lot of expense” he said.

While larger companies can hire software companies to develop sophisticated systems customized to a business’ needs, it’s a luxury not many can afford.

Even companies that have the expertise to integrate AI themselves pay a premium to do so.

Lita Global, for example, spends about $2,000 on AI every month, part of which goes to purchasing tokens for OpenAI’s application programming interface (API). APIs allow companies to build upon OpenAI’s models, instead of requiring companies to build the AI model from scratch.

AI can help improve early-life and elderly health care: Danone

However, as AI improves, the cost to use it is expected to drop. Research and advisory firm Gartner predicted in February that by 2027, the average prices of application programming interfaces for genAI will fall to less than 1% of the current average price for the same technology.

That could mean even greater affordability for smaller businesses adopting AI for their businesses.

Outlook for the region

In emerging markets such as those in Southeast Asia where labor costs are low, companies may feel less motivated to boost efficiency through adoption of technology. But technology can provide “much better [outcomes]” for existing business practices, said NUS Business School’s Wirtz. AI is just another way to adopt technology.

He compared it to the popularization of e-hailing services, which reduced the risk of tourists getting scammed by taxi drivers in foreign countries, as e-hailing apps could estimate the price of a journey.

And with a tech-savvy population of entrepreneurs in economies such as Vietnam, where labor costs are low, the excitement to adopt AI remains high, according to Parida.

“It’s a very hungry young people,” he said.

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Meta wins AI copyright case, but judge says others could bring lawsuits

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Meta wins AI copyright case, but judge says others could bring lawsuits

Meta CEO Mark Zuckerberg makes a keynote speech during the Meta Connect annual event, at the company’s headquarters in Menlo Park, California, on Sept. 25, 2024.

Manuel Orbegozo | Reuters


Meta on Wednesday prevailed against a group of 13 authors in a major copyright case involving the company’s Llama artificial intelligence model, but the judge made clear his ruling was limited to this case.

U.S. District Judge Vince Chhabria sided with Meta’s argument that the company’s use of books to train its large language models, or LLMs, is protected under the fair use doctrine of U.S. copyright law.

Lawyers representing the plaintiffs, including Sarah Silverman and Ta-Nehisi Coates, alleged that Meta violated the nation’s copyright law because the company did not seek permission from the authors to use their books for the company’s AI model, among other claims.

Notably, Chhabria said that it “is generally illegal to copy protected works without permission,” but in this case, the plaintiffs failed to present a compelling argument that Meta’s use of books to train Llama caused “market harm.” Chhabria wrote that the plaintiffs had put forward two flawed arguments for their case.

“On this record Meta has defeated the plaintiffs’ half-hearted argument that its copying causes or threatens significant market harm,” Chhabria said. “That conclusion may be in significant tension with reality.”

Meta’s practice of “copying the work for a transformative purpose” is protected by the fair use doctrine, the judge wrote.

“We appreciate today’s decision from the Court,” a Meta spokesperson said in a statement. “Open-source AI models are powering transformative innovations, productivity and creativity for individuals and companies, and fair use of copyright material is a vital legal framework for building this transformative technology.”

Though there could be valid arguments that Meta’s data training practice negatively impacts the book market, the plaintiffs did not adequately make their case, the judge wrote.

Attorneys representing the plaintiffs did not respond to a request for comment.

Still, Chhabria noted several flaws in Meta’s defense, including the notion that the “public interest” would be “badly disserved” if the company and other businesses were prohibited “from using copyrighted text as training data without paying to do so.”

“Meta seems to imply that such a ruling would stop the development of LLMs and other generative AI technologies in its tracks,” Chhabria wrote. “This is nonsense.”

The judge left the door open for other authors to bring similar AI-related copyright lawsuits against Meta, saying that “in the grand scheme of things, the consequences of this ruling are limited.”

“This is not a class action, so the ruling only affects the rights of these thirteen authors — not the countless others whose works Meta used to train its models,” he wrote. “And, as should now be clear, this ruling does not stand for the proposition that Meta’s use of copyrighted materials to train its language models is lawful.”

Additionally, Chhabria noted that there is still a pending, separate claim made by the plaintiffs alleging that Meta “may have illegally distributed their works (via torrenting).”

Earlier this week, a federal judge ruled that Anthropic‘s use of books to train its AI model Claude was also “transformative,” thus satisfying the fair use doctrine. Still, that judge said that Anthropic must face a trial over allegations that it downloaded millions of pirated books to train its AI systems.”

“That Anthropic later bought a copy of a book it earlier stole off the internet will not absolve it of liability for the theft, but it may affect the extent of statutory damages,” the judge wrote.

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