Tubi is a complimentary streaming service akin to Netflix, Hulu, and Amazon Prime Video. It boasts a substantial library of more than 20,000 movies and television shows available for streaming on your smart phone, smart TV, or streaming device.
As a free service, you’ll encounter ads while accessing the content. Tubi operates on an advertising-based model, which enables them to offer their wide-ranging collection at no cost. Content will be available from Lionsgate, NBCUniversal, Disney and Sony Pictures Entertainment.
It has been owned by Murdoch’s Fox Corporation since 2020. As of May 2024, the service boasts 80 million monthly active users in the U.S.
To put this figure into some perspective, the loss is comparable to the GDP output of a small country, such as Norway, Singapore, or the UAE, for example.
Global semiconductor stocks experienced volatility on Tuesday following a decline in Nvidia’s shares from the previous trading sessions.
Shares of chip firms in Europe and Asia fell in early trade as investors reacted to Nvidia losing more than $500 billion in market capitalization over three trading days. Some of the stocks recouped losses, however, as shares in the U.S. chipmaking giant recovered around 6 – 6.5% as of Tuesday 25th June 2024.
This follows a significant drop in Nvidia’s share value, which fell 13% over three consecutive sessions from the record highs achieved on Thursday 20th June 2024.
On Monday 24th June 2024, Nvidia’s stock closed down 6.7%, marking its second-largest decline of the year, yet the shares began to recover in early trading on Tuesday 25th June 2024.
Last week, the company surpassed Apple and Microsoft to become the most valuable U.S. company, achieving a market capitalization of over $3.4 trillion. However, by the end of Monday, Nvidia’s market value had declined by more than $540 billion from its intraday record on Thursday 20th June 2024.
Nvidia reported that the demand for its highly sought-after artificial intelligence graphics processing units (GPUs) continues to be strong.
Companies such as Microsoft, Google, Amazon, and Meta are investing billions of dollars in these chips to enhance their data centres and cloud services.
Nvidia’s shares surpassed $1,000 for the first time during extended trading on Wednesday 22nd May 2024, following the chip manufacturers report of fiscal first-quarter (Q1) earnings that exceeded analysts’ expectations.
Investors have been using Nvidia’s performance as a barometer for the AI industry’s growth, which has captivated the market over the past year. The robust results indicate that the demand for Nvidia’s AI chips continues to be strong. However, there may be an argument that it is time to take some profits from these massive gains. Can it continue its meteoric climb?
It was also announced that revenues from the upcoming next-generation AI chip, ‘Blackwell‘, are expected later in the year.
In extended trading, the stock increased by around 7%. Additionally, Nvidia announced a 10-for-1 stock split. Given the post-market activity, the shares are on track to reach a new high on Thursday 23rd May 2024.
Nvidia anticipates sales of $28 billion for the current quarter, surpassing Wall Street’s expectations of $26.61 billion sales, as reported – (Nvidia financial reports)
The company declared a net income of $14.88 billion, or $5.98 per share, a significant increase from $2.04 billion, or 82 cents per share, in the same period last year. (Nvidia financial reports)
Over the past year, Nvidia’s sales have surged, driven by purchases from tech giants like Google, Microsoft, Meta, Amazon, and OpenAI, which have invested billions in Nvidia’s GPUs. These high-end, expensive chips are essential for the development and deployment of artificial intelligence (AI) applications.
Nvidia’s primary business segment, data center sales, encompasses AI chips and other necessary components for operating large AI servers.
The revenue for Nvidia’s data centre sector soared over 400% compared to the previous year. This growth was attributed to the delivery of the company’s ‘Hopper’ graphics processors (GPU’s), including the H100 GPU.
It was also reported that Meta’s Lama 3, their newest large language model utilizing 24,000 H100 GPUs, as a notable income stream this quarter.
Amazon is reportedly set to launch an enhanced version of its long-standing voice assistant this year, which will be available for a monthly fee, according to sources.
This new service reportedly will not be part of the Amazon Prime subscription. The news emerges as OpenAI introduced a chatbot capable of engaging in two-way conversations, contrasting with Alexa’s current common uses such as setting kitchen timers and providing weather updates.
Now what’s wrong with that – that’s how I use my Alexa!
Anthropic, the artificial intelligence (AI) startup backed by Amazon, reported on Monday 13th May 2024 that it’s launching its generative AI assistant Claude in Europe on Tuesday 14th May 2024.
Claude.ai will be accessible to both individuals and businesses via the web and an iPhone app. While it is already free on both platforms in the U.K., Anthropic states that this marks the product’s inaugural launch for users in the EU and non-EU nations such as, Switzerland, Norway and Iceland.
Anthropic is introducing a paid subscription-based version of its Claude assistant, named Claude Pro, which will provide users with access to all its models, including the highly advanced Claude 3 Opus.
In its announcement about launching Claude in European countries, Anthropic emphasized security and privacy as central aspects.
Earlier this year, the EU enacted the first significant global regulatory framework to govern AI.
Amazon’s Q1 earnings and revenue exceeded expectations, emphasised by the expansion of its advertising and cloud computing sectors.
Earnings per share: 98 cents vs. 83 cents expected
Revenue: $143.3 billion vs. $142.5 billion expected
The operating income surged over 200% to $15.3 billion in the period, significantly exceeding revenue growth, indicating that the company’s cost-reduction strategies and efficiency improvements are enhancing its financial performance.
AWS contributed to 62% of the total operating profit. The net income also saw a more than threefold increase to $10.4 billion, or 98 cents per share, up from $3.17 billion, or 31 cents per share, in the previous year. There was a 13% rise in sales from $127.4 billion the previous year.
One year Amazon chart May 2023 – April 2024
One year Amazon chart May 2023 – April 2024
Amazon expects a continued rise in profitability for the Q2, albeit at a more consistent pace. The company projects its operating income to range from $10 billion to $14 billion, marking an increase from the previous year’s $7.7 billion.
It’s all about the customer
Amazon is dedicated to enhancing customer experiences daily through innovative and advanced products and services. This commitment extends to consumers, brands, sellers, enterprises, developers and content creators alike.
Jeff Bezos filed a statement indicating his sale of nearly 12 million shares of Amazon stock worth more than $2 billion
The Amazon executive chairman notified the U.S. SEC – Securities and Exchange Commission of the sale of 11,997,698 shares of common stock on the 7th and 8th February 2024.
The collective value of the shares of Amazon, which is based in Seattle where he founded the company in a garage around thirty years ago, was about $2.04 billion.
More to come
In a separate SEC filing, Bezos listed the proposed sale of 50 million Amazon shares on or around 7th February 2024 with an estimated market value of $8.4 billion.
Taxing decision?
Jeff Bezos moved from Seattle to Miami in November 2023, shortly before he announced his plan to sell up to 50 million Amazon shares by January 2025.
Florida does not have a capital gains tax, unlike Washington state, which imposes a 7% tax on any gains of more than $250,000 from the sale of stocks and bonds. Therefore, by moving to Florida, Bezos could save up to $600 million in taxes on his stock sale – more than enough for a luxury yacht and 2 or 3 more luxury properties.
But, of course, we do not know if this was the real reason for his move.
It was a good day of earnings for Big Tech companies.
Three of the Magnificent 7 results dominated the headlines: Meta, Amazon and Apple. Nasdaq and S&P 500 gained in ‘after the bell’ trading. This after a punishing day for Alphabet and Microsoft, despite good results.
Nasdaq 100 closed at: 17344 but climbed above 17500 in after-hours trading.
Wall Street seemed impressed with Meta’s results.
Meta
Shares of Meta surged 15% after the social-media giant defied analysts’ estimates. It posted earnings of $5.33 per share on revenue of $40.11 billion. The company also declared its first-ever dividend payment. Share buy-back was also announced.
Meta platforms Inc. One year chart
Meta platforms Inc. One year chart
The results show Meta’s online ad business continues to recover well from a terrible 2022.
Sales in the Q4 jumped 25% year on year.
Expenses decreased 8% year over year to $23.73 billion.
Amazon
Investors also enjoyed Amazon’s earnings, which easily topped Wall Street’s predictions. The ecommerce giant also provided a strong positive outlook. The stock jumped 7% in extended trading.
Amazon.com Inc. One year chart
Amazon.com Inc. One year chart
Q4 was a record-breaking Holiday shopping season in the U.S. and closed out a robust 2023 for Amazon. Amazon has much planned for 2024.
Apple
But Apple didn’t benefit from the same treatment despite posting strong results.
Apple Inc. One year chart
Apple Inc. One year chart
Apple also exceeded estimates, reporting revenue growth for the first time in a year. But shares slid more than 2% in extending trading after it posted a 13% decline in sales in China.
Apple’s outlook suggesting weak iPhones sales may have also disappointed investors.
U.S. microchip giant Advanced Micro Devices (AMD) is investing in AI PCs to take on the likes of Nvidia and Intel and Arm as the AI race gains momentum.
As the AI market expands so too will AI powered personal computer (PC). These are personal computers embedded with processors specifically designed to perform AI functions such as real-time language translation. Intel has already announced its AI powered chip for the PC.
Tech research firm Canalys in a December report said the boom in generative AI is expected to boost PC sales as consumers are seeking devices with AI features, predicting that 60% of the PCs shipped in 2027 will be AI-capable.
AI tech interest explodes
An explosion of interest in AI was sparked by the launch of ChatGPT in November 2022 as the chatbot went viral for its ability to generate human-like responses to users’ prompts.
Microsoft was quick to adopt the Technolgy and incorporate AI into its Bing search engine. Other companies such as Amazon, Alphabet (Google), Arm, Meta, Tesla and Apple are all heavily involved in AI development too.
The Magnificent Seven is a term coined to describe the seven most valuable and popularly owned tech companies in the U.S. stock market.
It was also a 1960’s movie…
The Seven
Apple (AAPL)
The world’s largest software company, known for its iPhone, iPad, Mac, Apple Watch, AirPods, and other devices, as well as its services such as iCloud, Apple Music, Apple TV+, and App Store.
Microsoft (MSFT)
The world’s largest software company, known for its Windows operating system, Azure cloud services, LinkedIn social media platform, Office professional software suite, and Xbox gaming brand.
Alphabet (GOOGL)
The parent company of Google, the world’s leading search engine, as well as other businesses such as YouTube, Google Cloud, Google Maps, Google Ads, and Waymo.
Amazon (AMZN)
The world’s largest online retailer, as well as a leading provider of cloud computing services through Amazon Web Services (AWS), and a major player in digital entertainment through Amazon Prime Video, Amazon Music, and Kindle.
Meta Platforms (META)
The former Facebook, the world’s largest social media network, as well as the owner of other popular platforms such as Instagram, WhatsApp, Messenger, and Oculus.
Nvidia (NVDA)
The world’s leading manufacturer of graphics processing units (GPUs), which are used for gaming, artificial intelligence, cloud computing, and cryptocurrency mining, as well as other products such as Nvidia Shield, GeForce Now, and Omniverse.
Tesla (TSLA)
The world’s most valuable automaker, known for its electric vehicles, battery products, solar panels, and self-driving technology, as well as its visionary founder and CEO, Elon Musk.
Market dominance
These seven companies are not only dominant in their respective fields, but also at the forefront of innovation and growth in the tech sector. They collectively make up some 30% of the S&P 500 index and more than half of the Nasdaq 100 index.
They have also delivered impressive returns for investors over the past five years, with Nvidia and Tesla leading the pack with more than 800% gains. The Magnificent Seven are often compared to the FAANG stocks, which include four of the seven companies, but exclude Microsoft, Nvidia, and Tesla, and include Netflix instead.
Some analysts suggest that the Magnificent Seven capture the current state and future potential of the tech industry. But is it now time to rotate out of tech into other areas that have been neglected. I wouldn’t be surprised to see the bull market charge on but with other ‘less’ loved companies leading the way.
It has been calculated that the combined market cap value of these seven companies is some $9 trillion.
In 1993, amidst the hustle and bustle of family life and work commitments, I distinctly recall contemplating that should I have any disposable income, I would invest it in these particular stocks.
I worked in tech running my own business and Microsoft was one of the businesses I wondered about, Apple was another and later Amazon too.
I never bought them, but had I have done, this is what would have happened.
Microsoft
Microsoft in 1993 was trading at around $2.35 per share. Today the company’s share price is trading at around $374.00 per share. So, had I bought $1,000 (adjusting for splits and dividends), my $1000 would be worth about $160,000 now. Had I bought $10,000 – I would have made just over $1 million.
Amazon
Had I bought Amazon a little later in 1997 and held it, a $1000 investment would now be worth a staggering $1.7 million (adjusting for splits and dividends). After the IPO and subsequent stock splits Amazon shares were trading at just 7 cents each according to Amazon’s website.
Apple
And as for Apple – a stock purchase in 1993 of $1000 would now be worth approximately $900,000 (not allowing for stock splits and dividends). Apple was trading at 22 cents per share in 1993.
The question is, if I had made the stock purchases – would I still be holding them long-term?
Amazon Web Services (AWS) announced Trainium2, a chip for training artificial intelligence (AI) models, and it will also offer access to Nvidia’s next-generation H200 Tensor Core graphics processing units.
Amazon’s AWS cloud department of the encompassing Amazon empire has announced new chips for customers to build and run artificial intelligence (AI) applications on, as well as plans to offer access to Nvidia’s latest chips.
Amazon Web Services is attempting to stand out as a cloud provider with a variety of cost-effective options. It won’t just sell cheap Amazon-branded products, though. Just as in its online retail marketplace, Amazon’s cloud will feature top-of-the-line products from other vendors, including highly sought after GPUs from top AI chipmaker Nvidia
Amazon’s dual-pronged approach of both building its own chips and letting customers access Nvidia’s latest chips might will help it against its top cloud computing competitor, Microsoft.
An old well established and trusted tech brand pivoting to AI that has a high dividend yield is IBM, which has been around for more than a century and is known for both its hardware and software products.
IBM is investing heavily in AI, cloud computing, and quantum computing, and has recently acquired several AI start-ups, such as Instana, Turbonomic, and Waeg.
IBM also has a partnership with OpenAI, one of the leading AI research organizations, to provide cloud infrastructure for its AI models.
Investors who love IBM expect the company to grow its earnings by around 10% annually over the next five years. Investors were also impressed with IBM’s dividend yield, which is currently around 4.5%. Dividends are a great way to generate passive income.
IBM is not the only tech company that is pivoting to AI. Google, Microsoft, and Anthropic are competing in the field of generative AI, which can create text, images, music, and more from natural language prompts.
Integrate generative AI
These companies are attempting to integrate generative AI into their products and services, such as search engines, maps, word processors, office applications, chatbots, and more. Generative AI is seen as a game-changer for many industries and applications, and could potentially disrupt the dominance of Big Tech.
Legacy companies can pivot to a platform model, which is a business strategy that connects producers and consumers of value through a digital interface. Platform companies like Facebook, Amazon, Google, and Tencent have created value at stunning rates, and have grown rapidly and own large market shares.
IBM mainframe from the 1970’s
Legacy companies can leverage their existing systems, such as customer relationships, data, and brand recognition, to create platforms that offer impressive and immersive products and services.
Other successful platform pivots are Disney+, which transformed Disney from a media producer to a media platform; Nike+, which connected Nike’s physical products with digital services; and John Deere, which created a platform for precision agriculture.
Apple and generative AI technology is a topic that has been generating a lot of interest and speculation lately.
According to various reports, Apple is working on developing its own large language model and chatbot, which could potentially enhance its products and services with new features and capabilities. However, some analysts and experts have also raised questions about whether Apple has missed an opportunity to be a leader in the generative AI field, as it seems to be lagging behind its competitors such as Google, Microsoft, and OpenAI.
Apple uses AI in its products but hasn’t launched a generative AI product along the lines of OpenAI’s ChatGPT or Google Bard. Instead, Apple’s AI is used for improving photos and autocorrecting text.
$1 billion per year plan
Apple is on track to spend $1 billion per year on developing its generative artificial intelligence products, Bloomberg reported.
Apple is looking to use AI to improve Siri, Messages and Apple Music.
The spending comes as the company plays catch-up to some competitors who have already debuted new AI products and features, such as Google, Microsoft and Amazon.
Apple was caught flat-footed when ChatGPT and other AI tools took the technology industry by storm.
Generative AI
Generative AI is a subfield of artificial intelligence that focuses on creating content such as text, images, videos, music, and more, based on data and algorithms. One of the most popular examples of generative AI is ChatGPT, a chatbot that can respond to questions and other prompts in a natural and human-like way.
Watercolour artwork impression – ChatGPT was released by OpenAI in 2022, and since then, it has been widely used and improved by various companies and researchers.
ChatGPT was released by OpenAI in 2022, and since then, it has been widely used and improved by various companies and researchers.
Apple slow response
Apple, on the other hand, has been relatively quiet about its generative AI efforts, until recently. In October 2023, Bloomberg reported that Apple was internally testing a ‘ChatGPT-like’ chatbot nicknamed ‘Apple GPT’, but it had not devised a clear strategy for releasing generative AI tools to the public. Apple’s CEO Tim Cook also confirmed that the company was working on generative AI for years, but it was approaching it ‘really thoughtfully and think about it deeply’ because of the potential risks and challenges.
Potential challenges Apple faces in developing and deploying generative AI
Privacy
Apple has always been more cautious than its competitors in handling user data, and it has built its reputation on being a privacy-focused company. However, generative AI requires a lot of data to train and improve its models, which could pose a dilemma for Apple. How can it balance the need for data with the respect for user privacy? How can it ensure that its generative AI does not leak or misuse personal information?
Design
Apple is known for its elegant and intuitive design philosophy, which applies to both its hardware and software products. However, generative AI is a complex and unpredictable technology, which could challenge Apple’s design principles. How can it make its generative AI features easy to use and understand for its customers? How can it avoid confusing or misleading users with its generative AI outputs?
Ethics
Apple has always been mindful of the social and ethical implications of its products, and it has often taken a stance on issues such as human rights, environmental sustainability, and diversity. However, generative AI could raise new ethical concerns, such as bias, misinformation and manipulation. But then that is a common problem for all generative AI systems.
Generative AI could raise new ethical concerns, such as bias, misinformation and manipulation.
These are some of the questions that Apple needs to answer before it can launch its generative AI products to the public. It is possible that Apple is taking its time to address these issues carefully and thoroughly, as it has done in the past with other technologies such as Face ID or Apple Pay. However, it is also possible that Apple has missed an opportunity to be a pioneer in the generative AI field, as it has done in the past with other technologies such as smart speakers or cloud computing.
While Apple is working on its generative AI projects internally, its competitors are already offering generative AI.
Google
Google has integrated its large language model LaMDA into various products and services, such as Google Assistant, Google Photos, Google Docs, Google Translate etc. LaMDA can generate natural and conversational responses to any query or prompt, as well as create images and videos based on text descriptions.
Microsoft
Microsoft has acquired OpenAI’s ChatGPT technology and made it available through its Azure cloud platform. ChatGPT can be used by developers and businesses to create chatbots, voice assistants, content generators, and more. Microsoft has also integrated ChatGPT into some of its products such as Outlook, Teams, PowerPoint, and more.
Amazon
Amazon has launched Alexa Conversations, a feature that allows Alexa users to have more natural and engaging conversations with the voice assistant. Alexa Conversations can also leverage Amazon’s vast e-commerce data to provide personalized recommendations and suggestions to users.
These are just some examples of how generative AI is being used by Apple’s competitors.
Robot chatting to human chatbot online
Apple has missed an opportunity to be a leader in the generative AI field by being too slow or too cautious in developing and deploying its own generative AI products.
However, it is highly likely that Apple is waiting for the right moment to surprise everyone with its innovative and unique generative AI features that will set it apart from its competitors.
These are the seven largest U.S. listed companies in the technology sector.
Apple, Microsoft, Amazon, Alphabet, Nvidia, Tesla and Meta Platforms.
According to a report released Monday 2nd October 2023, these tech’ stocks have seen their valuation drop relative to the median stock in the S&P 500, making them more attractive for investors. The report says that the Magnificent 7 trade at 1.3 times their PEG ratio (price-to-earnings-to-long-term growth), versus 1.9 for the median S&P 500 stock.
This is the cheapest valuation in over six years – time to buy yet?
The report also highlights some positive drivers for these stocks, such as their strong sales growth, their ability to beat expectations, and their resilience to rising interest rates.
However, some analysts also warn that the dominance of these stocks could pose a risk for the broader market if something bad happens to tech’.
E-commerce conglomerate Amazon announced on Monday 25th September 2023 that it will invest up to $4 billion in artificial intelligence (AI) firm Anthropic, a rival to ChatGPT developer OpenAI, and take a minority ownership position in the company.
The move further enforces Amazon’s aggressive AI push as it aims to keep pace with rivals such as Microsoft and Alphabet’s Google.
The two firms reportedly said that they are forming a strategic collaboration to advance generative AI, with the startup selecting Amazon Web Services as its primary cloud provider.
The Magnificent Seven is a term to describe seven tech’ stocks that have been surging in 2023.
Meta Platforms (formerly Facebook), the social media giant that also owns Instagram, WhatsApp, and Oculus.
Apple, the maker of the iPhone, iPad, Mac, Apple Watch, AirPods, and other popular devices and services including cloud and Apple TV streaming service.
Amazon, the e-commerce leader that also operates AWS, Prime Video, Alexa, and Whole Foods.
Alphabet, the parent company of Google, YouTube, Gmail, Google Cloud, and Waymo.
Microsoft, the software company that owns Windows, Office, Azure, LinkedIn, Xbox, and Teams.
Nvidia, the semiconductor company that produces graphics cards, gaming devices, data center solutions, and AI platforms.
Tesla, the electric vehicle maker that also develops solar panels, batteries, and autonomous driving technology.
Dominant
These seven stocks are considered to be dominant in their respective fields and have strong growth prospects driven by innovation and artificial intelligence (AI).
They have outperformed the broader market and attracted many investors who are looking for exposure to the tech’ sector. Some analysts believe that these stocks will continue to lead the market in the future, while others caution that they may face regulatory challenges, competition, or valuation issues.
Approximate combined market cap of the Magnificent Seven tech stocks
The approximate combined market cap value of the Magnificent Seven as of September 2023 is approximately $11.8 trillion.
Apple: $2.5 trillion
Microsoft: $2.3 trillion
Alphabet: $1.9 trillion
Amazon: $1.7 trillion
Nvidia: $0.8 trillion
Meta Platforms: $0.9 trillion
Tesla: $0.7 trillion
Note that these values will change over time as the stock prices fluctuate.
A way to trade the tech sector is through funds
There are many funds that can trade tech stocks, depending on your investment objectives, risk tolerance, and preferences.
Technology mutual funds: These are funds that invest in a diversified portfolio of technology companies across different industries, such as software, hardware, internet, cloud, biotech, and more. Technology mutual funds can offer exposure to the growth potential of the tech sector, as well as reduce the volatility and risk of investing in individual stocks.
Some examples of technology mutual funds are Fidelity Select Technology Portfolio (FSELX), Columbia Global Technology Growth Fund (CGTYX), and Schwab U.S. Large-Cap Growth Index Fund (SCHG).
Which tech fund to invest in?
Technology exchange-traded funds (ETFs): These are funds that track an index of technology stocks and trade on an exchange like a stock. Technology ETFs can offer low-cost and convenient access to the tech sector, as well as allow investors to choose from different themes, such as cybersecurity, artificial intelligence (AI), cloud computing and more.
Some examples of technology ETFs are Invesco QQQ Trust (QQQ), Technology Select Sector SPDR Fund (XLK), and VanEck Vectors Semiconductor ETF (SMH).
Technology index funds: These are funds that replicate the performance of a specific technology index, such as the Nasdaq 100, the S&P 500 Information Technology Index, or the Morningstar U.S. Technology Index. Technology index funds can offer broad and passive exposure to the tech sector, as well as low fees and high tax efficiency.
Some examples of technology index funds are Fidelity NASDAQ Composite Index Fund (FNCMX), Vanguard Information Technology Index Fund Admiral Shares (VITAX), and iShares Morningstar U.S. Technology ETF (IYW).
NOTE: These are not recommendations. Investments may go up or down. Your money is at risk!
Nvidia shares rose 4.2% Tuesday 29th August 2023 to close at a record high, after the company announced a partnership with Google that could expand distribution of its artificial intelligence technology (AI).
The stock’s bountiful run continued, now up 234% in 2023, making it by far the best performer in the S&P 500. Facebook parent Meta is second in the index, up 148% so far this year.
The record close comes less than a week after the company said quarterly revenue doubled from a year earlier and gave a forecast indicating that sales this period could rise 170% on an annual basis. The day after the better-than-expected earnings report, the stock climbed to a record intraday high of $502.66 before declining later in the afternoon.
Nvidia’s business is booming because its graphics processing (GPU’s) are being gobbled up by cloud companies, government agencies and startups to train and deploy generative AI models like the technology deployed in OpenAI’s ChatGPT as fasta as Nvidia can make them.
NVIDIA stock chart
Nvidia announcment
On Tuesday 29th August 2023, Nvidia CEO Jensen Huang appeared at a Google conference to announce an AI agreement between the two companies.
Through the partnership, Google’s cloud customers will have greater access to technology powered by Nvidia’s powerful H100 GPUs.
‘Our expanded collaboration with Google Cloud will help developers accelerate their work with infrastructure, software and services that supercharge energy efficiency and reduce costs’, the Nvidia CEO reportedly said in a blog post.
Nvidia’s GPUs are also available on competing cloud platforms from Amazon and Microsoft.
Arm is a British semiconductor and software design company that is known for its Arm processors, which are widely used in smartphones, tablets, laptops, and other devices. Arm was founded in 1990 as a joint venture between Acorn Computers, Apple Computer, and VLSI Technology. The company was originally called Advanced RISC Machines, but later changed its name to Arm Ltd in 1998.
In 1985, the first Arm silicon chip was created by Acorn engineers Sophie Wilson and Steve Furber, who designed a 32-bit processor with a simple and elegant instruction set.
In 1990, Arm was spun off from Acorn as a separate company, with Apple as a major investor. Arm’s first product was the ARM6 processor, which was used in Apple’s Newton personal digital assistant.
Impression of the Apple Newton PDA device
In 1993, Arm introduced the ARM7 processor, which became one of the most successful embedded processors in history. It was used in devices such as the Nokia 6110 mobile phone, the Nintendo Game Boy Advance, and the Lego Mindstorms robotics kit.
In 1994, Arm launched the ARM9 processor family, which offered higher performance and lower power consumption than previous generations. The ARM9 was used in devices such as the Sony PlayStation Portable, the Palm Treo smartphone, and the Amazon Kindle e-reader.
In 1997, Arm introduced the ARM10 processor family, which featured a superscalar architecture and a floating-point unit. The ARM10 was used in devices such as the Apple iPod, the Samsung Galaxy S smartphone, and the Raspberry Pi computer.
In 1998, Arm changed its name from Advanced RISC Machines to Arm Ltd, reflecting its global expansion and recognition.
In 1999, Arm launched the ARM11 processor family, which featured a vector floating-point unit and a TrustZone security extension. The ARM11 was used in devices such as the iPhone 3G, the Nintendo DS, and the Raspberry Pi Zero.
In 2000, Arm became a public company, listing on the London Stock Exchange and the Nasdaq. The company raised £213 million in its initial public offering.
In 2001, Arm introduced the Cortex processor family, which offered a range of performance, power, and cost options for different applications. The Cortex processors are used in devices such as the Samsung Galaxy S10, the Apple Watch, and the Tesla Model 3.
In 2005, Arm acquired Artisan Components, a provider of physical intellectual property (IP) for chip design. This enabled Arm to offer a complete solution for system-on-chip (SoC) development.
In 2006, Arm announced the Mali graphics processing unit (GPU) family, which complemented its CPU offerings with high-performance graphics capabilities. The Mali GPUs are used in devices such as the Huawei Mate 20 Pro, the Oculus Quest, and the Samsung Smart TV.
Artistic image of ARM chip
In 2009, Arm partnered with IBM, Samsung, Texas Instruments, and others to form the Linaro consortium, which aimed to improve the Linux software ecosystem for Arm-based devices.
In 2010, Arm unveiled the Cortex-A15 processor, which was the first Arm processor to support virtualization and big.LITTLE technology. The Cortex-A15 was used in devices such as the Google Nexus 10, the LG G3, and the Nintendo Switch.
In 2011, Arm announced the Cortex-M0+ processor, which was the world’s most energy-efficient microcontroller. The Cortex-M0+ was used in devices such as the Arduino Nano 33 IoT, the Fitbit Flex 2, and the Nest Thermostat.
In 2012, Arm launched the Cortex-A53 and Cortex-A57 processors, which were the first Arm processors to support the 64-bit ARMv8 architecture. The Cortex-A53 and Cortex-A57 were used in devices such as the iPhone 6s, the Samsung Galaxy S6 Edge+, and the Microsoft Surface Pro X.
In 2013, Arm acquired Geomerics, a developer of real-time lighting technology for video games. This enhanced Arm’s graphics portfolio with dynamic illumination and global illumination effects.
In 2014, Arm introduced the Cortex-A72 processor, which delivered a 50% performance improvement over the previous generation. The Cortex-A72 was used in devices such as the Huawei P9, the Xiaomi Mi 5s Plus, and the Amazon Fire HD 10.
In 2015, Arm announced the Cortex-A35 processor, which was the most efficient Arm processor for smartphones and tablets. The Cortex-A35 was used in devices such as the Nokia 2.1, the Samsung Galaxy J2 Core, and the Lenovo Tab M7.
In 2016, Arm was acquired by SoftBank Group for £24.3 billion, becoming a subsidiary of the Japanese conglomerate. The deal was motivated by SoftBank’s vision of investing in technologies that would drive the future of artificial intelligence (AI), internet of things (IoT), and smart cities.
In 2017, Arm launched Project Trillium, a suite of machine learning (ML) solutions that included an ML processor , an object detection processor , and an open-source software framework. The Project Trillium products aimed to enable low-power and high-performance ML applications on edge devices.
In 2018, Arm unveiled the Cortex-A76 processor , which offered a 35% performance boost over its predecessor. The Cortex-A76 was used in devices such as the OnePlus 7T, the Huawei MateBook D14, and the Acer Chromebook Spin 13.
In 2019, Arm announced the Cortex-A77 processor , which improved on its predecessor with a higher clock speed, a larger cache, and better branch prediction . The Cortex-A77 was used in devices such as the Samsung Galaxy S20, the Asus ROG Phone II, and the Lenovo Yoga C940.
In 2020, Arm introduced the Cortex-X1 processor , which was its most powerful CPU design to date. The Cortex-X1 was designed to deliver peak performance for premium device , such as flagship smartphones, laptops and gaming consoles. The Cortex-X1 was used in devices such as the Samsung Galaxy S21 Ultra, the Xiaomi Mi 11, and the Google Pixel 6.
In 2021, Arm launched the Cortex-A78C processor , which was optimized for high-performance computing (HPC) applications. The Cortex-A78C featured up to eight CPU cores , a larger L3 cache, and support for ECC memory. The Cortex-A78C was used in devices such as the Samsung Galaxy Book Pro, the HP Elite Folio , and the Acer Chromebook Spin 513.
Microchip
In 2022, Arm unveiled the Cortex-A710 processor, which was its first big core to support the Armv9 architecture. The Cortex-A710 offered a 30% energy efficiency improvement over its predecessor, as well as enhanced security and ML features. The Cortex-A710 was used in devices such as the OnePlus 10 Pro, the Huawei MatePad Pro 2, and the Microsoft Surface Laptop Studio.
In 2023, Arm announced the Immortalis GPU family , which was its next-generation graphics solution that included hardware-based ray-tracing and variable rate shading capabilities . The Immortalis GPUs aimed to deliver realistic and immersive graphics for gaming, VR and AR applications on mobile devices . The Immortalis GPUs were used in devices such as the Samsung Galaxy S22 Ultra , the Sony Xperia 1 IV, and the Oculus Quest 3.
Powerful world presence
Arm is a leading semiconductor and software design company that has revolutionized the computing industry with its innovative and efficient processor architectures. Arm’s processors power billions of devices across various domains, such as mobile, IoT, AI, HPC, and gaming. Arm has been at the forefront of technological advancements for over three decades, delivering performance, energy efficiency, and security to its customers and partners.
Arm is a subsidiary of SoftBank Group and has a massive global presence.
Amazon is one of the leading companies in the field of artificial intelligence (AI) and has been developing its own custom chips to power its AI applications and services.
Amazon’s AI chips are designed to perform tasks such as natural language processing, computer vision, speech recognition, and machine learning inference and training.
AI chips created by Amazon
AZ2: This is a processor built into the Echo Show 15 smart display and powers artificial intelligence tasks like understanding your voice commands and figuring out who is issuing those commands. The AZ2 chip also enables features such as visual ID, which can recognize faces and display personalized information on the screen.
Inferentia: This is a high-performance chip that Amazon launched to deliver low-cost and high-throughput inference for deep learning applications. Inferentia powers Amazon Elastic Compute Cloud (EC2) Inf1 instances, which are optimized for running inference workloads on AWS. Inferentia also powers some of Amazon’s own services, such as Alexa, Rekognition, and SageMaker Neo.
Trainium: This is a chip that Amazon designed to provide high-performance and low-cost training for machine learning models. Trainium will power Amazon EC2 Inf2 instances, which are designed to train increasingly complex models, such as large language models and vision transformers. Trainium will also support scale-out distributed training with ultra-high-speed connectivity between accelerators.
Despite advancements is Amazon chasing to keep up?
Amazon is racing to catch up with Microsoft and Google in the field of generative AI, which is a branch of AI that can create new content or data from existing data. Generative AI can be used for applications such as natural language generation, image and video synthesis, text summarization, and personalization.
AI models from Amazon
Titan: This is a family of large language models (LLMs). Titan models can generate natural language texts for various domains and tasks, such as conversational agents, document summarization, product reviews, and more. Titan models are trained on a large and diverse corpus of text data from various sources, such as books, news articles, social media posts, and product descriptions.
Powerful chips for artificial intelligence (AI)
Bedrock: This is a service that Amazon created to help developers enhance their software using generative AI. Bedrock provides access to pre-trained Titan models and tools to customize them for specific use cases. Bedrock also allows developers to deploy their generative AI applications on AWS using Inferentia or Trainium chips.
Generative AI
Amazon’s CEO, Andy Jassy in the past said he thought of generative AI as having three macro layers: the compute, the models, and the applications. He said that Amazon is investing heavily in all three layers and that its custom chips are a key part of its strategy to provide high-performance and low-cost compute for generative AI. He also said that Amazon is not used to chasing markets but creating them, and that he believes Amazon has the best platform for generative AI in the world.
Inferentia and Trainium, offer AWS customers an alternative to training their large language models on Nvidia GPUs, which have been getting difficult and expensive to procure.
‘The entire world would like more chips for doing generative AI, whether that’s GPUs or whether that’s Amazon’s own chips that we’re designing’, Amazon Web Services CEO Adam Selipsky is reported to have said. ‘I think that we’re in a better position than anybody else on Earth to supply the capacity that our customers collectively are going to want’.
Fast actors
Yet others have acted faster, and invested more, to capture business from the generative AI boom. When OpenAI launched ChatGPT in November 2022, Microsoft gained widespread attention for hosting the chatbot, and investing a reportedly whopping $13 billion in OpenAI. It was quick to add the generative AI models to its own products, incorporating them into Bing in February 2023.
That same month, Google launched its own large language model, Bard, followed by a $300 million investment in OpenAI rival Anthropic.
AI Chat Bot robot
It wasn’t until April 2023 that Amazon announced its own family of large language models, called Titan, along with a service called Bedrock to help developers enhance software using generative AI.
Amazon is not used to chasing markets. Amazon is used to creating markets. And for the first time for some time, they find themselves on the back foot and working to play catch up.
And Meta?
Meta also recently released its own LLM, Llama 2. The open-source ChatGPT rival is now available for people to test on Microsoft’s Azure public cloud.