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Nvidia is all in on AI, as it announces a historic quarter with record-breaking results.

In the wake of Wednesday’s announcement that Nvidia’s earnings have significantly outperformed expectations, Reuters has disclosed that Nvidia’s CEO, Jensen Huang, foresees the enduring growth of the AI industry extending well into the next year. As an affirmation of this perspective, Nvidia has committed to repurchasing $25 billion worth of shares, a value now triple what it was before the surge of generative AI enthusiasm.

In a press release showcasing Nvidia’s financial achievements, including a remarkable quarterly revenue of $13.51 billion—marking a 101 percent increase from the prior year and an 88 percent surge from the previous quarter—Huang declared with enthusiasm, “A new era of computing has dawned.” He went on to note that businesses worldwide are shifting from conventional computing to accelerated computing and generative AI.

For those just tuning in, Reuters describes Nvidia as having a “near monopoly” on hardware that accelerates the training and deployment of neural networks, which are the driving force behind contemporary generative AI models. The company commands a substantial 60-70 percent share of the AI server market. Notably, its data center GPU lines excel in conducting the billions of matrix multiplications crucial for running neural networks due to their parallel architecture. What began as graphics accelerators for video games now power the generative AI boom.

Among Nvidia’s most popular AI hardware offerings are the A100 and H100 data center GPUs. Moreover, Nvidia has introduced the GH200 “Grace Hopper” chipset, a combination of the H100 and a CPU, which fuels Nvidia’s range of computer systems. These are not your typical consumer-grade gaming GPUs like the GeForce RTX 4090; The Verge reports that the H100 chip retails for around $40,000 and boasts the capability to execute a significantly higher volume of calculations per second.

The demand for GPUs in AI applications is immense, with Nvidia’s second-quarter data center revenue reaching an impressive $10.32 billion, dwarfing its consumer gaming revenue of $2.49 billion. In March, reports indicated that OpenAI’s widely-used AI assistant, ChatGPT, was anticipated to harness as many as 30,000 Nvidia GPUs for its operations, although precise figures from the company remain undisclosed. Microsoft is also leveraging data centers equipped with “tens of thousands” of GPUs to power its implementations of OpenAI’s technology, which it is currently integrating into Microsoft Office and Windows 11.

As Huang succinctly puts it, “This is not a one-quarter thing.” The AI surge appears set to continue its trajectory well into the foreseeable future.

Nvidia’s dominant position in the market has left competitors like AMD scrambling to catch up. Currently, Nvidia’s lead appears almost insurmountable, as evidenced by its historic achievement in May when it became the first-ever $1 trillion chip company.

While Huang’s decision to repurchase stock at a time when prices are at their highest carries inherent risk, it underscores his unwavering confidence in Nvidia’s sustained success. The strong demand for Nvidia’s chips has provided the financial means to execute this strategy, as demonstrated by the company’s impressive second-quarter performance. Notably, their adjusted gross margins, a key financial metric measuring profitability after accounting for the cost of goods sold, surged to 71.2 percent. This figure significantly outpaces the typical gross margins of semiconductor companies, which usually fall between 50 and 60 percent, as highlighted by Reuters.

In an interview with Reuters, Huang identified two pivotal factors propelling Nvidia’s current triumph: the increasing shift from data centers centered around CPUs to those anchored by Nvidia’s graphics processing units (GPUs), and the growing utilisation of generative AI systems like ChatGPT.

“These two fundamental trends are driving all that we’re witnessing, and we’re about a quarter into this transformation,” he explained to Reuters. “While it’s challenging to predict how many more quarters lie ahead, this fundamental shift isn’t ephemeral; it’s a long-term evolution.”

However, as with any burgeoning industry, there’s the specter of a potential downturn. Every boom ultimately faces the risk of a bust, and Nvidia may not be immune. Reuters reported that some analysts doubt the limitless demand for Nvidia’s GPU chips. Dylan Patel from SemiAnalysis, quoted by the news agency, suggested that many tech companies are riding the wave of AI hype, purchasing Nvidia GPUs speculatively without a clear plan to monetize generative AI. This behavior could be likened to a billion-dollar case of FOMO (Fear of Missing Out).

“They must overinvest in GPUs or risk missing the boat,” warned Patel. “At some point, the genuine use cases will become apparent, and many players may curtail their investments, although others will likely continue to accelerate their commitment.”

Another potential hurdle on the horizon is product shortages. Reuters indicated that Huang regards securing the necessary supplies for producing its expensive server hardware as Nvidia’s most significant risk. The company’s most significant sales success in the current quarter is the HGX system, a supercomputer built around its H100 GPUs, which requires sourcing numerous individual components.

“We’re receiving substantial support from our supply chain,” Huang assured Reuters in an interview. “Yet, it’s an intricate supply chain. People might assume it’s just a GPU chip, but it’s an exceedingly complex GPU system. It weighs 70 pounds, comprises 35,000 components, and costs $200,000.”

Furthermore, obtaining the H100 chips themselves has become increasingly challenging. Presently, the demand for high-powered GPUs far exceeds the supply, potentially posing a bottleneck to the pace of AI innovation. Nevertheless, this scarcity may also stimulate the development of innovative techniques to maximize the utility of available GPU power.

The latest contender to ChatGPT, known as Claude 2, has officially entered the open beta testing phase

On Tuesday, Anthropic unveiled Claude 2, a substantial language model (LLM) akin to ChatGPT, proficient in coding, text analysis, and composition creation. In contrast to the initial Claude version launched in March, users can now explore Claude 2 freely on a new beta website. Additionally, it is accessible as a commercial API for developers.

Anthropic asserts that Claude is engineered to emulate conversations with a supportive colleague or a personal assistant. The new iteration incorporates valuable feedback from users of the preceding model, emphasizing its ease of interaction, clear articulation of reasoning, reduced propensity for generating harmful content, and an extended memory capacity.

Anthropic asserts that Claude 2 showcases notable advancements in three crucial domains: coding, mathematics, and reasoning. They note, “Our latest model achieved a 76.5% score on the multiple-choice section of the Bar exam, a marked improvement from Claude 1.3’s 73.0%.” Furthermore, when compared to college students applying for graduate programs, Claude 2’s performance places it in the top 10% on the GRE reading and writing examinations, with a comparable standing to the median applicant in quantitative reasoning.

Claude 2 boasts several significant improvements, including an expanded input and output capacity. As we’ve previously discussed, Anthropic has conducted experiments enabling the processing of prompts containing up to 100,000 tokens, allowing the AI model to analyze extensive documents, such as technical manuals or entire books. This extended capability also applies to the length of its generated content, facilitating the creation of longer documents.

Regarding its coding prowess, Claude 2 has exhibited a notable increase in proficiency. It achieved a higher score on the Codex HumanEval, a Python programming assessment, elevating from 56 percent to an impressive 71.2 percent. Similarly, in the GSM8k test, which assesses grade-school math problems, Claude 2 improved its performance from 85.2 to 88 percent.

A primary focus for Anthropic has been refining its language model to reduce the likelihood of generating “harmful” or “offensive” outputs in response to specific prompts, although quantifying these qualities remains subjective and challenging. An internal red-teaming evaluation revealed that “Claude 2 delivered responses that were twice as benign as Claude 1.3.”

Claude 2 is now accessible to the general public in the US and UK, serving individual users and businesses through its API. Anthropic has reported that companies like Jasper, an AI writing platform, and Source graph, a code navigation tool, have already integrated Claude 2 into their operations.

It’s crucial to keep in mind that while AI models like Claude 2 are proficient at analyzing lengthy and intricate content, Anthropic acknowledges their limitations. After all, language models occasionally generate information without factual basis. Therefore, it’s advisable not to rely on them as authoritative references but rather to utilize them for processing data you provide, especially if you possess prior knowledge of the subject matter and can verify the results.

Anthropic emphasizes that “AI assistants are most beneficial in everyday scenarios, such as summarizing or organizing information,” and cautions against their use in situations involving physical or mental health and well-being.

LSIGraph Launches New Contextual Terms Feature For Improved Content Optimization

With its latest update, LSIGraph encourages its users to add contextual terms for improved SEO content, allowing higher search engine rankings and traffic growth.

Kuala Lumpur, Malaysia – November 16, 2022

In its determined effort to help its users climb search rankings and grow traffic, LSIGraph launches a new update on its flagship SEO keyword research tool. This update adds a new feature to its Content Writer tool called the “Contextual Terms”. 

This newly added feature to their Content Writer Tool suggests a list of Contextual Terms that its user can add to their content to increase its contextual relevance. It also tells them the optimal usage frequency of a contextual term to further optimize their content. Additionally, the innovational feature shows its users examples of use from other top-ranking pages for more insight into its usage.

The need for this new update arose from the team’s own research into Google’s never-ending ranking factors and what would help the most in creating the best SEO content. With their research showing better SERP ranking results by building content context, LSIGraph adds this feature to help its users better optimize their content.

In order to suggest contextual terms to its users, LSIGraph looks at top-ranking pages of a target keyword and extracts the commonly used and most impactful words. By using more contextual terms in their content, writers can build more context and attract more relevant traffic.

“Our studies show that producing contextually-sound content boosts a website’s ranking on search engines and drives relevant traffic,” says Andy, the founder of LSIGraph. “We will continuously perform research and hope to roll out more updates to help our users maximize their content’s ranking potential.”

For more information on LSIGraph’s current and future updates, readers can check out their announcement page here.

About LSIGraph

LSIGraph is an SEO tool with a mission to help its users climb search engine rankings and grow their traffic. This tool focuses on three areas of SEO success: keyword targeting, content writing and optimization, and content mapping. The three main tools guide a user throughout the whole process of producing highly-optimized content, from keyword research to content writing and content planning.

Today, LSIGraph continues to pave its way to the top of SEO tools, with more than 160,000 subscribers utilizing it for their SEO marketing strategies. With different subscription plans available, LSIGraph strives to match every marketer’s different needs. For more information, readers can take a look at their pricing plans.

Contact Info:

Name: Sara Saila


Organization: LSIGraph


Grab Announces A $988 Million Financial Loss In Q3 Due To A Drop In Ride-Hailing During Lockdowns

The Singapore unicorn expects its SPAC deal to finalize in Q4 of this year.

Grab, the Southeast Asian unicorn reported a net loss of $988 million for the July-September quarter, increased from a loss of $621 million a year earlier, as increased COVID-19 control measures in the area impacted its core ride-hailing business.

The Singaporean digital tech business, a significant startup in the area, offers ride-hailing, delivery, and banking services through what it calls a “superapp” approach.

Singapore, Malaysia, Indonesia, Vietnam, Thailand, the Philippines, Cambodia, and Myanmar are among the countries it operates.

On Thursday, Grab also stated that its proposed merger with a particular purpose acquisition company, Altimeter Growth Corp., located in the United States, “continues to advance and is slated to complete in the fourth quarter of 2021.”

The deal values Grab at roughly $40 billion and allow the business to be listed on the Nasdaq.

Grab said noncash expenditures such as accrued interest, stock-based compensation, and fair value fluctuations on assets account for a substantial portion of the massive loss for the quarter.

However, several Southeast Asian countries took severe restrictions to control coronavirus spread during the three months through September, creating a “difficult operating environment,” Grab said in a statement.

According to the company, revenue fell 9% to $157 million in the third quarter “as a result of the predicted fall in mobility owing to the severe lockdowns in Vietnam,” according to the company.

Revenue from the ride-hailing business fell 26% to $88 million, while revenue from the delivery business increased 58% year on year to $49 million.

Financial services revenue, such as its e-wallet, climbed 11% to $14 million.

The accounting revenue for Grab is shown net of incentives for drivers, retailers, and customers.

Consumer incentives more than quadrupled to $271 million in the third quarter, indicating a competitive business climate in the region.

Due to its delivery and banking services growth, its gross merchandise value (the entire value of transactions completed through Grab’s platform) climbed 32% to $4 billion in the quarter.

“Despite severe lockdowns in Vietnam and heightened limitations across the region in the third quarter as a result of COVID-19, we performed successfully on our superapp strategy and produced excellent growth,” said CEO Anthony Tan in a statement.

“With a recovery insight and the progressive reopening of economies giving tailwinds to our company, we are doubling down on investments that will help us grab a larger part of the possibilities before us and open up new addressable markets for Grab, such as grocery.”

Separately, Tan stated during an investor webcast that the firm anticipates a significant rebound in the ride-hailing sector in the fourth quarter, particularly in Indonesia, Malaysia, and Vietnam, as vaccination rates rise in the area.

Carousell Achieved Unicorn Status, With a Valuation of US$1.1B Thanks to a US$100M Investment From Korea’s STIC Investments

Carousell Group, a Singapore-based classifieds startup with operations in nine countries throughout Asia and Canada, revealed yesterday that it had secured US$100 million (RM415 million) to accelerate expansion.

The media announcement made no mention of a listing. However, media sources from June have connected it to a prospective US listing via SPAC (Special Purpose Acquisition Company).

Quek Siu Rui, co-founder, and CEO of Carousell, mentioned that the pandemic has proven its mission to inspire the world to start selling, and buying secondhand is more relevant than ever.

People are utilizing our platforms to make it more feasible for one another, whether via shared interests, making ends meet, affording what they require, or just because it is more sustainable.

They believed that the increased adoption of digital experiences is an opportunity for them to double down on their recommerce efforts, focusing on convenience and trust to unleash step-change growth in their community.

The investment by STIC validates their goal and strategic direction.  Also, they envision increasing their investments in recommerce across new categories and markets, and they will continue to look for opportunistic acquisitions to help them scale up.

Jason Cho, Managing Director of STIC Investments, stated they have been keeping an eye on Carousell and are thrilled to be partnering with a significant share in its development narrative.

Carousell continues to see tremendous user growth as it transforms the recommerce industry by introducing new features to build trusted marketplaces and improve the overall user experience.

The team and he are convinced that Carousell will be at the heart of the secondhand economy in this region at a time when a growing number of socioeconomic and environmentally concerned customers are turning toward a circular economy.

Besides that, Cho will join the Carousell Board as part of the financing round.

Since its founding in 2012, the Group has served tens of millions of consumers in eight Southeast Asian and Taiwan markets through the brands Carousell, (in Malaysia), Cho Tot (Vietnam), and OneKyat (Myanmar).

The last three locations were formerly held by Telenor Group, a Norwegian telecom, before the two companies merged in late 2019.

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