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Nvidia navigating challenges amidst an AI spending boom

Naushad K. Cherrayil
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Nvidia navigating challenges amidst an AI spending boom
  • Company’s optimistic outlook, articulated by CEO Jensen Huang, has provided a much-needed boost to investor confidence following a quarterly performance that, while solid, did not meet the lofty expectations set by Nvidia’s historical achievements.
  • Generates $11b in revenue from Blackwell AI chips in the fourth quarter.

In the rapidly evolving landscape of artificial intelligence (AI), Nvidia Corporation has emerged as a pivotal player, particularly with the recent launch of its Blackwell product lineup.

The company’s optimistic outlook, articulated by Chief Executive Officer Jensen Huang, has provided a much-needed boost to investor confidence following a quarterly performance that, while solid, did not meet the lofty expectations set by Nvidia’s historical achievements.

With $11 billion in revenue attributed to Blackwell in the fourth quarter, Nvidia has characterised this product as experiencing the “fastest product ramp” in its history, a testament to the robust demand for its cutting-edge technology.

Despite this encouraging news, the broader AI industry faces significant uncertainties. Nvidia’s stock has experienced fluctuations this year, primarily driven by concerns that data centre operators may curtail their spending.

The emergence of Chinese startup DeepSeek has further compounded these anxieties, as its announcement of a low-cost chatbot development model raised fears about the potential diminishment of demand for Nvidia’s powerful AI chips.

In this precarious environment, Nvidia’s assertion of sustained growth, albeit without the explosive results characteristic of its past performances, is particularly noteworthy.

Data centre generates more revenue

For the upcoming fiscal first quarter, which concludes in April, Nvidia has projected sales of approximately $43 billion, slightly above analysts’ average estimate of $42.3 billion.

However, the company also indicated that gross profit margins may fall short of expectations, a point that could temper investor enthusiasm.

Notably, while Nvidia’s fourth-quarter sales of $39.3 billion exceeded analysts’ estimates, the margin of this outperformance was the narrowest observed since February 2023, reflecting a potential plateau in the company’s meteoric growth trajectory.

Furthermore, the profit of 89 cents per share, adjusted for certain items, surpassed Wall Street’s expectations of 84 cents, showcasing the company’s resilience in a challenging market.

Nvidia’s data centre unit remains its dominant revenue stream, generating $35.6 billion in sales, which exceeded the average estimate of $34.1 billion.

AI spending boom is far from over

However, the gaming segment, once the cornerstone of Nvidia’s business, reported sales of only $2.5 billion, falling short of the anticipated $3.02 billion.

Its data centre division alone now has more revenue than rivals Intel and Advanced Micro Devices have in total, combined.

The shift underscores the company’s transition towards AI and data centre solutions as the primary drivers of growth. The automotive segment, contributing $570 million, reflects Nvidia’s strategic diversification into new markets.

As Nvidia navigates these challenges, the company’s track record of consistently exceeding analysts’ estimates—having missed expectations only once in the past five years—sets a high bar for its future performance.

The recent selloff in AI-related shares, particularly following DeepSeek’s announcement, underscores the volatility inherent in the sector. Nvidia’s staggering loss of $589 billion in market capitalisation in a single trading day serves as a stark reminder of the market’s sensitivity to emerging competitors and shifting technological paradigms.

Nevertheless, key partnerships with major clients, such as Microsoft Corp, suggest that the momentum of AI investment remains intact. These companies have indicated their commitment to capital expenditure plans, reinforcing the notion that the AI spending boom is far from over.

Huang’s role as a global advocate for AI technology has positioned Nvidia at the forefront of this revolution, and his belief that AI is still in its nascent stages of integration into the economy may resonate with investors seeking long-term growth.

Amazon takes a leap into GenAI with its Alexa+ voice assistant

Mohammed Fahad
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Amazon takes a leap into GenAI with its Alexa+ voice assistant
  • Designed to understand users’ preferences, schedules and smart home devices.
  • New iteration allows Alexa to store personalised information, such as dietary preferences and entertainment choices, and perform tasks like making dinner reservations and sending reminders.
  • With approximately 500 million Alexa-capable devices already in circulation, the potential for Alexa+ to reshape the voice assistant landscape is immense.

Amazon unveiled a significant overhaul of its Alexa voice assistant, marking the first major update since its inception over a decade ago. The transformation, branded as Alexa+, integrates generative artificial intelligence (AI) to enhance the assistant’s functionality and user experience.

The initiative underscores Amazon’s substantial investment in Alexa, which has amounted to billions of dollars since its launch in 2014, with the dual aim of embedding the service across various devices and driving sales on its e-commerce platform.

Panos Panay, Amazon’s head of devices and services, highlighted the extensive capabilities of Alexa+, stating that it is designed to understand users’ preferences, schedules, and smart home devices. This new iteration allows Alexa to store personalised information, such as dietary preferences and entertainment choices, and perform tasks like making dinner reservations and sending reminders.

Such advancements aim to create a more intuitive and engaging user experience, positioning Alexa as an indispensable tool in daily life.

Enhancing user engagement

The introduction of Alexa+ is particularly noteworthy as it comes at a time when competition in the voice assistant market is intensifying. Competitors like Apple and Google have already integrated advanced AI features into their respective assistants, Siri and Google Assistant.

Amazon’s decision to launch Alexa+ as a premium service, free for Amazon Prime members and priced at $19.99 per month for non-members, reflects a strategic move to enhance user engagement while also generating additional revenue.

However, the rollout of Alexa+ is not without challenges. Early demonstrations revealed instances of the assistant providing incorrect answers or lagging in response times, raising concerns about its reliability. The need for repeated prompts during the presentation suggests that while the technology has evolved, it may still require refinement to meet user expectations fully.

As Amazon prepares for a broader release of the service, addressing these issues will be crucial to maintaining consumer trust and interest.

With approximately 500 million Alexa-capable devices already in circulation, the potential for Alexa+ to reshape the voice assistant landscape is immense. This revamp represents not only a significant opportunity for Amazon to solidify its position in the market but also a considerable financial risk if the service fails to deliver on its promises.

As the company embarks on this new chapter, the success of Alexa+ will hinge on its ability to seamlessly integrate generative AI, thereby enhancing its functionality and ultimately enriching the user experience.

Salesforce growth hinges on success of Agentforce

Ana Mary Joseph
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Salesforce growth hinges on success of Agentforce
  • Forecasts weak annual profit and revenue as leadership transitions create uncertainty.
  • Salesforce faces stiff competition from industry giants such as Microsoft and ServiceNow in the AI space.

Salesforce Inc., a prominent player in the customer relationship management (CRM) software sector, provided a fiscal-year revenue forecast that fell short of market expectations, casting a shadow over the anticipated growth driven by its new artificial intelligence product, Agentforce.

The San Francisco-based company projected revenue between $40.5 billion and $40.9 billion for the year ending January 2026. While the adjusted operating margin is expected to be approximately 34 per cent, slightly exceeding the analyst average of 33.9 per cent, the overall sentiment surrounding Salesforce’s financial outlook remains cautious.

The introduction of Agentforce, designed to automate customer service tasks with minimal human intervention, represents Salesforce’s strategic pivot towards AI-driven solutions. Launched in October, the product aims to enhance operational efficiency and customer engagement.

Facing stiff competition

However, Salesforce faces stiff competition from industry giants such as Microsoft Corp. and ServiceNow Inc., both of which are pursuing similar AI initiatives. Despite this competitive landscape, Salesforce has reported a significant uptake of Agentforce, claiming to have “closed 5,000” deals for the product.

CEO Marc Benioff highlighted the success of Agentforce during a recent interview, noting its implementation by notable clients such as Pfizer Inc., Singapore Airlines, and Equinox.

Financially, Salesforce reported a 7.6 per cent increase in revenue for the fiscal fourth quarter ending January 31, totaling $9.99 billion. However, this marks the third consecutive quarter of single-digit growth, a notable decline from the company’s historical performance characterised by robust expansion.

Profit figures also surpassed expectations, with earnings of $2.78 per share compared to the average estimate of $2.61. Nevertheless, the mixed results led to a tepid response from investors, with shares experiencing a modest decline in after-hours trading, closing at $307.33.

Over the past year, Salesforce’s stock has gained only 2.3 per cent, trailing behind many of its software industry peers.

Market uncertainty

Investor sentiment has been further complicated by recent changes in Salesforce’s executive leadership. The departures of longtime Chief Financial Officer Amy Weaver and Chief Operating Officer Brian Millham have raised concerns about the company’s strategic direction.

Robin Washington, a seasoned technology executive and board member since 2013, has been appointed to the newly created role of Chief Financial and Operations Officer.

Such leadership transitions often create uncertainty, particularly during a period when the company is simultaneously navigating a challenging market environment and implementing significant organisational changes.

Salesforce has made the difficult decision to cut more than 1,000 jobs in an effort to realign its resources toward AI-focused initiatives. This move underscores the company’s commitment to prioritising its investments in artificial intelligence, which has garnered increasing attention and resources across the technology landscape.

Additionally, Salesforce has taken strategic steps to diversify its infrastructure partnerships, awarding a substantial $2.5 billion cloud contract to Alphabet Inc.’s Google, thereby expanding its operational framework beyond its traditional reliance on Amazon Web Services.

Which AI chatbot shares most data with third parties?

Naushad K. Cherrayil
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Which AI chatbot shares most data with third parties?
  • Google Gemini collects the most user data among AI chatbots, gathering 22 out of 35 types of data.
  • Apple’s App Store privacy guidelines outline 35 distinct types of data that applications may potentially accumulate.

In the ever-evolving digital landscape, artificial intelligence (AI) has permeated various facets of human interaction, offering an impressive array of services through AI chatbots.

These virtual assistants, designed to engage users through natural language processing and machine learning, have rapidly gained popularity. However, beneath the surface of convenience and user engagement lies a disconcerting reality: the extent to which these chatbots collect and manage user data.

Recent findings from a study conducted by cybersecurity firm Surfshark shed light on a pressing issue – the pervasive data collection practices adopted by these AI platforms, some of which extend to sharing users’ information with third parties.

The research by Surfshark highlights a rather alarming trend among the leading AI chatbots available on the Apple App Store. While these applications promise enhanced interaction and personalised assistance, they simultaneously initiate a complex relationship with user privacy.

According to the study, all ten of the most popular AI chatbots not only engage in gathering various types of user data but to exacerbate concerns regarding privacy, 30 per cent of them reportedly share this data with external parties.

Such practices often cater to the interests of targeted advertising and data measurement enterprises, as well as third-party brokers.

Raises eyebrows

A closer examination of the data collection practices reveals that Apple’s App Store privacy guidelines outline 35 distinct types of data that applications may potentially accumulate. On average, these chatbots assimilate around 11 different types of user data, which could range from personal identifiers to usage patterns.

Notably, Google’s Gemini chatbot stands out in the realm of data collection, with an extensive repertoire of 22 types of assimilated data. This includes not only the user’s precise location but also a plethora of other sensitive information, such as contact details—name, email address, and phone number—as well as user-generated content, browsing history, and stored contacts.

Such exhaustive data accumulation brings forth substantial implications surrounding user autonomy and control over personal information.

Critics of these extensive data collection initiatives have voiced concerns that such practices can be perceived as excessive and intrusive. The recent discourse surrounding digital privacy underscores a growing unease among users about the extent of surveillance they unwittingly invite into their lives.

As Surfshark researchers aptly noted, the accumulation and potential commodification of their personal data can instigate apprehension among individuals who prioritise safeguarding their digital identities. This discourse raises compelling ethical questions regarding the balance between providing personalised service and the right of users to retain control over their personal information.

In contrast, OpenAI’s ChatGPT has purportedly adopted a less invasive approach to data collection, reportedly gathering only ten types of data. This includes crucial identifiers, usage data, and user content, yet this chatbot has elected not to engage in third-party advertising, which adds a layer of assurance regarding user privacy.

Monetisation of user data

Nevertheless, it must be noted that ChatGPT does maintain a chat history, although users are afforded the flexibility to enable temporary chats that auto-delete after 30 days or to request the removal of their personal data from training datasets. Such options contribute positively to the discourse on user agency, but they also evoke further scrutiny regarding what constitutes an adequate privacy policy.

The analysis of other chatbots presents a similarly troubling picture. The Chinese chatbot DeepSeek is characteristic of an operational model that collects 11 unique types of user data and maintains chat history without explicit transparency on data usage policies.

The assertion that user information may be retained “for as long as necessary” and stored on servers located in the People’s Republic of China raises critical concerns about data sovereignty and international privacy standards.

This underscores the imperative for individuals to contemplate the implications of utilizing applications developed in jurisdictions with distinct regulatory frameworks.

Chatbots such as Copilot, Poe, and Jasper AI also reveal a concerning trend towards the accumulation of data that holds potential for tracking users.

Jasper, for instance, collects product interaction data and advertising data, which can be utilised for targeted advertisement or sold to data brokers.

The monetisation of user data significantly complicates the nexus of personal privacy and corporate interests, necessitating a comprehensive approach to user education and regulation in the burgeoning field of AI.

Microsoft claims quantum computing is “years, not decades” away

Ana Mary Joseph
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Microsoft claims quantum computing is “years, not decades” away
  • Microsoft claims that its Majorana 1 chip is less prone to such errors compared to its competitors, a claim supported by a forthcoming scientific paper in Nature.
  • Majorana 1 features fewer qubits than competing chips from Google and IBM.

Microsoft unveiled its Majorana 1 chip, asserting that practical quantum computing is now “years, not decades” away.

The announcement positions Microsoft alongside tech giants such as Google and IBM, who have similarly suggested that a transformative shift in computing technology is imminent. Quantum computing promises to revolutionise various fields, particularly in executing complex calculations that would otherwise take classical computers millions of years.

This potential extends to groundbreaking discoveries in medicine and chemistry, where the vast combinations of molecular structures often overwhelm traditional computational capabilities.

The promise of quantum computing, however, is accompanied by substantial challenges, particularly concerning the stability and reliability of qubits—the fundamental units of quantum information.

Unlike classical bits, which can exist in a state of either zero or one, qubits can represent multiple states simultaneously, enabling quantum computers to process information at unprecedented speeds. Yet, this advantage is tempered by the qubit’s susceptibility to errors and difficulties in control.

Reduced error

Microsoft has claimed that its Majorana 1 chip is less prone to such errors compared to its competitors, a claim supported by a forthcoming scientific paper in the esteemed journal Nature.

The discourse surrounding the timeline for the practical application of quantum computing remains contentious among industry leaders. Jensen Huang, CEO of Nvidia, expressed scepticism, suggesting that quantum technology is still two decades away from surpassing traditional computing capabilities.

In contrast, Google has posited that commercial applications of quantum computing could emerge within five years, while IBM anticipates large-scale quantum computers to be operational by 2033.

This divergence in predictions underscores the uncertainty inherent in the field of quantum computing, a domain marked by rapid advancements and evolving understanding.

Microsoft’s Majorana 1 chip is particularly noteworthy due to its reliance on the Majorana fermion, a subatomic particle theorised in the 1930s. The properties of Majorana fermions are believed to contribute to reduced error rates in quantum computations, a critical factor for the viability of quantum systems.

Raises cybersecurity concerns

The chip’s development, which has spanned nearly two decades, utilises a combination of indium arsenide and aluminum, employing superconducting nanowires to observe and manipulate these elusive particles.

Notably, while Majorana 1 features fewer qubits than competing chips from Google and IBM, Microsoft asserts that its design will require fewer qubits to achieve practical utility due to its enhanced error resilience.

Despite the excitement surrounding Majorana 1, Microsoft has not specified a timeline for scaling the chip into a fully operational quantum computer.

Nevertheless, the company remains optimistic, suggesting that the transition from theoretical exploration to practical application is imminent.

Jason Zander, Microsoft’s executive vice president overseeing long-term strategic initiatives, characterized the development of Majorana 1 as a “high risk, high reward” endeavour.

He emphasised the innovative nature of the project, noting that the team had to pioneer new methodologies to fabricate the chip at the atomic level.

The implications of Microsoft’s advancements in quantum computing extend beyond computational prowess; they also raise critical concerns regarding cybersecurity.

Current encryption systems largely rely on the assumption that classical computers cannot feasibly break complex codes within a reasonable timeframe.

However, the advent of powerful quantum computers poses a significant threat to these systems, as they could potentially crack existing encryption methods with alarming efficiency. This duality of promise and peril encapsulates the profound impact that quantum computing could have on society.

Apple unveils budget-friendly AI iPhone to win back mid-market

Mohammed Fahad
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Apple unveils budget-friendly AI iPhone to win back mid-market
  • By modernising its low-end offering and integrating in-house technology, Apple aims to revive growth and strengthen its competitive position against emerging rivals.
  • The iPhone 16e may not encompass all the premium features of its higher-end siblings, it embodies Apple’s strategic vision of making advanced technology accessible to a broader audience, ensuring its relevance in an increasingly diverse smartphone market.

In a bid to rejuvenate its growth trajectory following a lackluster holiday season, Apple Inc. has announced the introduction of the iPhone 16e, a new low-end smartphone priced at $599.

Set to go on sale on February 28, with preorders beginning on February 21, the iPhone 16e replaces the iPhone SE, which was priced at $429. The strategic move represents a significant shift in Apple’s approach to its low-end smartphone segment, marking the most substantial changes since the original iPhone SE was launched in 2016.

The iPhone 16e includes the same A18 chip used in the $799 iPhone 16 and $899 iPhone 16 Plus.

The iPhone 16e showcases several modern features aimed at attracting consumers seeking an affordable yet technologically advanced device. Notably, Apple has removed the traditional home button, introducing a larger 6.1-inch screen complemented by Face ID technology.

In-house cellular modem chip

The device boasts a 48-megapixel camera and is powered by the same A18 chip found in the iPhone 16, ensuring that users experience high performance and efficiency. Additionally, the inclusion of a USB-C charging port aligns the iPhone 16e with industry standards, reflecting Apple’s commitment to modernisation.

Perhaps the most groundbreaking aspect of the iPhone 16e is the introduction of Apple’s in-house cellular modem chip, named C1. This development marks a pivotal transition away from reliance on Qualcomm, a long-standing supplier.

Apple’s investment in this technology, which has reportedly involved a multibillion-dollar commitment over seven years, underscores the company’s ambition to enhance its hardware capabilities and reduce dependency on external suppliers.

The C1 modem is expected to facilitate seamless connectivity, although it currently does not support mmWave technology, which is essential for ultra-fast 5G downloads in major urban areas.

Nevertheless, Apple anticipates that the new modem will improve battery life, offering up to 26 hours of video playback—an improvement over the third-generation iPhone SE’s 15 hours.

Better battery life

Despite these advancements, the iPhone 16e does have limitations compared to its more expensive counterparts. It lacks features such as the Dynamic Island interface, MagSafe wireless charging, and the faster-refreshing ProMotion display found in the iPhone 16 Pro models.

Additionally, it is equipped with a single back camera, which may deter some photography enthusiasts. However, these compromises are likely intended to maintain a competitive price point while still offering a compelling entry-level option.

Apple’s decision to discontinue the current iPhone SE and iPhone 14 alongside the launch of the iPhone 16e indicates a strategic consolidation of its product lineup. This move is particularly crucial as the company faces challenges in key markets, notably in China, where sales fell by 11% in the last quarter.

The iPhone 16e is designed to provide Apple with a more appealing offering in the lower end of the smartphone market, an area that has become increasingly competitive with the rise of local brands like Huawei and Xiaomi.

The launch of the iPhone 16e is part of a broader strategy that includes several anticipated design changes throughout the year, signaling Apple’s commitment to innovation and adaptation in a rapidly evolving market.

As the company seeks to bolster its smartphone business, which experienced a one per cent decline in sales during the holiday quarter, the iPhone 16e represents a calculated effort to engage customers who prioritise both affordability and cutting-edge technology.

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