Albert Einstein 1879 – 1955
‘Intelligence is not the ability to store information, but to know where to find it’.
Baidu’s Ernie bot is top app on Apple’s app store in China
Top of the apps on Apple app store
Baidu’s Ernie bot is a ChatGPT-like chatbot that can generate natural and fluent text based on user input. It is one of the latest artificial intelligence applications from Baidu, a Chinese tech giant that specializes in search engine and AI development.
Ernie bot was released to the public on 31st August 2023, after getting approval from the Chinese regulators under the new AI regulations and quickly became the most popular app on Apple’s app store in China, surpassing other local generative AI models.
Ernie bot can be accessed through an app or a website, and users can chat with it on various topics, such as news, entertainment, sports, and education. Ernie bot is also able to learn from human feedback and improve its foundation models.
Nvidia’s stock at record high after Google AI deal
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.
Nvidia blasts off into AI superstardom
Technology giant Nvidia reports its sales have hit a record after more than doubling as demand for its artificial intelligence (AI) chips take off!
It figures
The company says revenue jumped to above $13.5bn (£10.6bn) for the three months to the end of June. Nvidia also expects sales to perform very well in the current quarter and plans to buy back $25bn of its stock. The firm’s shares rose by more than 6.5% in extended trading in New York, adding to their huge gains this year. Nvidia also said it expects revenue of around $16bn for the three months to the end of September 2023.
That is substantially higher than Wall Street expected and would equate to a rise of around 170%, compared to the same time last year.
Even before 23rd August’s figures, Nvidia’s stock price had more than tripled for the year, making it the top performer in the S&P 500. It’s share price jumped to around $500 after hours, a level that would mark a record if it closes there on 24th August 2023. Its prior closing high was $474.94 on 18th July 2023.
‘A new computing era has begun’, Nvidia’s chief executive, Jensen Huang, said in a statement. ‘Companies worldwide are transitioning from general-purpose to accelerated computing and generative AI’, he reportedly added.
Strong performance
The strong performance was driven by Nvidia’s data centre business, which includes AI chips.
Revenue for that unit came in at more $10.3bn, a rise of more than 170% from year ago, as cloud computing service providers and large consumer internet companies snapped up its next-generation processors.
This year, Nvidia’s stock market value has jumped to more than $1 trillion as its shares more than tripled in value, mking it the fifth publicly traded U.S. company to join the so-called ‘Trillion dollar club’, along with Apple, Amazon, Alphabet and Microsoft.
AI ‘mania’ helps Nvidia
Nvidia have been making micro chips for a long time and it’s only really been in the last couple of years that the market has caught on.
Nvidia was originally known for making the type of computer chips that process graphics, particularly for computer games. They have been making chips for a long time and have now become the leader in AI chip design and manufacture.
Now Nvidia’s hardware is the foundation for most AI applications, with one report suggesting it had cornered 95% of the market for machine learning.
ChatGPT which generates human-like responses to user queries within seconds was trained using 10,000 of Nvidia’s graphics processing units clustered together in a supercomputer belonging to Microsoft.
AI products are expected to dramatically change how we use computers and the role they play in our lives.
ChatGPT shows left-wing bias according to UK researchers
AI Chatbot ChatGPT reportedly has a political bias
ChatGPT, the popular artificial intelligence chatbot, shows a significant and systemic left-wing bias, UK researchers have found. According to the new study by the University of East Anglia, this includes favouring the Labour Party and President Joe Biden’s Democrats in the U.S.
Concerns about an inbuilt political bias in ChatGPT have been raised before, notably by SpaceX and Tesla tycoon Elon Musk, but the academics said their work was the first large-scale study to find proof of any favouritism.
Lead author o the report reportedly warned that given the increasing use of OpenAI’s platform by the public, the findings could have implications for upcoming elections on both sides of the Atlantic. Any bias in a platform like this is a concern’, he said. If the bias were to the right, we should be equally concerned.
Sometimes people forget these AI models are just machines. They provide very believable, digested summaries of what you are asking, even if they’re completely wrong. And if you ask it ‘are you neutral’, it says ‘oh I am!’ Just as the media, the internet, and social media can influence the public, this could be very harmful. I have personally witnessed incorrect responses from ChatGPT where the AI ‘system’ 100% believed ‘it’ was correct and would not engage in a debate as ‘it’ was right!
How was ChatGPT tested for bias?
The chatbot, which generates responses to prompts typed in by the user, was asked to impersonate people from across the political spectrum while answering dozens of ideological questions. These questions ranged from radical to neutral, with each ‘individual’ asked whether they agreed, strongly agreed, disagreed, or strongly disagreed with a given statement.
Its replies were compared to the default answers it gave to the same set of queries, allowing the researchers to compare how much they were associated with a particular political stance.
Each of the more than 60 questions was asked 100 times to allow for the potential randomness of the AI, and these multiple responses were analysed further for signs of bias.
Dr Motoki described it as a way of trying to simulate a survey of a real human population, whose answers may also differ depending on when they’re asked.
Bias was descovered in the Chatbot repsonses.
A brief history of ARM
Brief ARM history
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.
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.
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.
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.
Hundreds caught breaking the law on AI camera system in Cornwall UK
A new artificial intelligence (AI) road safety camera system has been deployed on the A30 near Launceston, Cornwall, by Devon and Cornwall Police.
The camera system uses AI to detect potential offences such as using mobile phones or not wearing seatbelts while driving. The camera system can capture ultra clear images of the car’s interior and send them to a human reviewer who can issue a warning letter or a notice of intended prosecution, depending on the severity of the offence.
Hundreds caught
The camera system is the first of its kind to be used in the UK and it has caught almost 300 drivers breaking the law in the first three days of its operation. The camera system is part of the Vision Zero South West project, which aims to reduce road deaths and serious injuries in Devon and Cornwall. The project conducted a 15-day trial of a similar vehicle-based system last year and detected 590 seat belt and 45 mobile phone offences across various roads in the two counties.
The police hope that the new technology will help deter drivers from using their phones or not wearing their seatbelts, which are both dangerous and illegal behaviours that put people’s lives at risk.
The road safety system is from tech’ firm Acusensus.
The police have reportedly said they are ‘disappointed’ by the number of people not wearing seatbelts orand using their mobile ‘phones when drving.
Amazon – leading or competing?
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.
- 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.
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.
The AI battle continues…
Hackers to compete for $20 million prize
The U.S. cyber hacker challenge is a new initiative launched by the Biden administration in August 2023 to use artificial intelligence (AI) to protect critical U.S. infrastructure from cybersecurity risks.
The challenge will offer $20 million in prize money and includes collaboration from leading AI companies Anthropic, Google, Microsoft and OpenAI, who will make their technology available for the competition. The challenge was announced at the Black Hat USA hacking conference in Las Vegas.
The competition will consist of three stages
- Qualifying event in the spring of 2024
- Semifinal at DEF CON 2024
- Final at DEF CON 2025
The competitors will be asked to use AI to secure vital software and open source their systems so that their solutions can be used widely (does that create a risk in itsellf)? The top three teams will be eligible for additional prizes, including a top prize of $4 million for the team that best secures vital software.
The challenge aims to explore what’s possible when experts in cybersecurity and AI have access to a suite of cross-company resources. The U.S. government hopes that the promise of AI can help further secure critical U.S. systems and protect Americans from future cyber attacks!
Limitations and risks using AI for security
However, there are flaws and drawbacks of using AI for cybersecurity, both for the attackers and the defenders.
- Lack of transparency and explainability: AI systems are often complex and opaque, making it difficult to understand how they make decisions or what factors influence their outputs. This can lead to trust issues, ethical dilemmas, and legal liabilities.
- Overreliance on AI: AI systems are not infallible and may make mistakes or produce false positives or negatives. Relying too much on AI, without human oversight or verification can result in missed threats, erroneous actions, or unintended consequences.
- Bias and discrimination: AI systems may inherit or amplify human biases or prejudices that are present in the data, algorithms, or design of the systems. This can result in unfair or discriminatory outcomes, such as excluding certain groups of people from access to services or opportunities, or targeting them for malicious attacks.
- Vulnerability to attacks: AI systems may be susceptible to adversarial attacks, such as data poisoning, model stealing, evasion, or exploitation. These attacks can compromise the integrity, availability, or confidentiality of the systems, or manipulate them to produce malicious outputs.
- High cost: Developing and maintaining AI systems for cybersecurity requires a lot of resources, such as computing power, memory, data, and skilled personnel. These resources may not be easily accessible or affordable for many organizations or individual.
These are some of the flaws of using AI for cybersecurity, but they are not insurmountable. With proper research, regulation, education, and collaboration, AI can be a powerful ally in enhancing cybersecurity and protecting against cyber threats – that is until it takes over, but that will never happen… will it?
U.S. to ban some U.S. investments in China tech sector
The U.S. will ban American investment in some areas of China’s high-tech sector, including artificial intelligence, adding to strained relations between the two superpowers.
U.S. firms will also be invited to disclose what investments they make in China in high-tech sectors.The much-anticipated move gives the U.S. government new power to screen foreign dealings by private companies. The U.S. said the measure would be narrowly targeted. However, it is poised to further chill economic relations between the world’s two largest economies. China has reportedly said it was ‘very disappointed‘. The U.S. ‘has continuously escalated suppression and restrictions on China‘. He added that White House claims that the US was not seeking to hurt China’s economy or separate the two countries did not match its actions. ‘We urge the US side to honour its words‘.
Biden order
The order by U.S. President Biden formally kicks off the push to introduce rules to restrict, even prevent American businesses from investing in firms from ‘countries of concern‘ that are active in advanced semiconductors, quantum computing and certain areas of artificial intelligence.
The government will also require U.S. firms to notify the Treasury Department of investments in firms working on a wider range of artificial intelligence and semiconductor technology.
The rules are not expected to apply to ‘portfolio’ investments, in which firms invest passively in companies via the stock market, but are focused on active investments made by private equity and venture capital businesses. They will now enter a public ‘reflection’ period, which is expected to further clarify what kinds of investments are off-limits. The rules are not expected to go into effect for sometime yet. This new ‘order’ is quite a big deal.
In a briefing with reporters, senior administration officials said the measure was a ‘national security action, not an economic one‘. They said the U.S. remained committed to open investment.
Investment control
Controls on outbound investment are rare among advanced economies, currently present only in Japan and Korea, according to a 2022 report.
In the U.S., prior restrictions on China trade have relied on limiting sales of sensitive technology by U.S. firms and screening Chinese investments in American companies. The Trump administration had also barred investments in firms tied to China’s military.
The latest measure has widespread support in Washington, where it is seen as fixing a regulatory gap concerning financial flows that risks allowing American money and know-how to to flow into China.
International support
The U.S. has been trying to build international support for the investment curbs with some signs of success.
Prime Minister Rishi Sunak in May 2023 said the UK government would consider curbs on outbound investment; the European Commission put forward a proposal focused on investments in sensitive technologies earlier this summer. It is not clear how significantly the order would affect flows of investment.
China was the number two destination for foreign investment in 2022, behind the U.S., but many reports suggest money flowing into the country from the U.S. and elsewhere has dropped sharply as geopolitical relations sour. In the UK, a recent survey by the Institute of Directors found that one in five UK importers had already switched investments away from the country due to geopolitical tensions.
China has responded to the curbs with its own rules, including limits on exports of some critical minerals used to make computer chips.
Treasury Secretary Janet Yellen, who visited China in July 2023 in an attempt to ease tensions, said last month she did not think the coming curbs would have a fundamental impact on the investment climate in the country.
Will these measures likely damage the U.S. in the future by escalating issues and restricting the U.S. from other shared advancements in technology – only time will tell.
Tech’ rivalry
U.S. and China are two of the world’s leading powers in artificial intelligence (AI) and semiconductors, which are essential components for many AI applications such as self-driving cars, smart phones, and cloud computing. However, the two countries have also been engaged in a fierce competition and rivalry over these technologies, as they seek to gain an edge in innovation, security, and economic growth. Some of the issues that have caused tensions between U.S. and China include trade disputes, intellectual property theft, cyberattacks, human rights violations, and military expansion.
AI chips
AI semiconductors are designed to perform complex calculations and tasks that require high levels of intelligence, such as natural language processing, computer vision, and machine learning.
These chips can be classified into two types: general-purpose chips that can run various AI algorithms, and specialized chips that are optimized for specific AI functions or domains.
The race is on…
Meta (Facebook) Posts Strong Wall Street Gain in 2023 – its year of efficiency
Meta Platforms, Inc. (Nasdaq: META), formerly known as Facebook, has seen its stock price soar in 2023, a straight nine month gain in a massive turnaround after a dismal performance in 2022.
Meta is the parent company of social media apps such as Facebook, Instagram, WhatsApp and Messenger, as well as the Oculus VR headset and other ventures.
Year of efficiency
Meta’s founder and CEO Mark Zuckerberg has declared 2023 as the ‘Year of Efficiency‘ for the company, as it tries to cut costs and streamline its operations. The company has also announced layoffs of about 10% of its workforce in 2022 and 2023, as part of its restructuring efforts.
Meta’s stock has almost doubled since January, making it among the top performers on the S&P 500. The company has also seen a boost in the number of daily active users on Facebook, reaching two billion as of the end of December 2022. Meta’s net worth is currently at $89.9 billion, making Zuckerberg the 12th wealthiest person on the planet, according to Bloomberg’s Billionaire Index.
Surge
Meta’s stock surge comes after a sharp decline in 2022, when the company faced regulatory scrutiny, public backlash and technical glitches over its plans to expand into the metaverse, a virtual reality world where people can interact with each other and through digital content.
Meta’s stock plummeted by over 60% last year, as Zuckerberg struggled to sell Wall Street on his vision for the future of social media.
Future
Meta is still betting on the metaverse as its long-term goal, and has been investing heavily in AI, VR and AR technologies. The company is reportedly working on a new social media app called ‘Instagram for your thoughts‘, which would allow users to share their thoughts and emotions using brain-computer interfaces.
The app could launch as soon as next month, according to latest reports.
The metaverse is coming!
Google says people should use its search engine to check whether information provided by its Chatbot, Bard, is actually accurate
Accuracy
According to a recent news article, Google says people should use its search engine to check whether information provided by Bard is actually accurate, as it may display inaccurate or offensive information that doesn’t represent Google’s views. Just Google views I wonder…?
Google’s UK boss Debbie Weinstein said Bard was not really the place that you go to search for specific information, but rather an experiment best suited for collaboration around problem solving and creating new ideas.
Hallucinate
According to an Android Authority article, both Bard and ChatGPT can hallucinate or confidently lie when asked about obscure topics. Bard does offer a link to search results and will sometimes cite a source or two. However, Google states that Bard can even lie about its own inner workings so you cannot trust everything it says…?
Testing… 1… 2… 3…?
According to a report by Marie Haynes, Bard predicts it will generate accurate responses 85% of the time by September 2023, but in an experiment, it posted an accuracy score of 63%, meaning it had incorrect information in more than 1/3 of its responses
Early days, or habouring a problem for the future?
Elon Musk launches xAI, a new AI company to understand reality
The entrepreneur
Elon Musk, the billionaire entrepreneur behind Tesla, SpaceX and Neuralink, has revealed his latest venture: xAI, a new artificial intelligence company that aims to “understand the true nature of the universe”.
Musk announced the formation of xAI on Wednesday on Twitter and on the company’s official website, which features a minimalist design and a brief introduction.
Link to website: xAI: Understand the Universe
To understand the universe – a big task
“Today we announce the formation of xAI,” the website states. “The goal of xAI is to understand the true nature of the universe.”
The website also lists 12 members of the xAI team, including Musk himself as the director. The team consists of researchers and engineers who have worked at leading AI firms such as Google’s DeepMind, OpenAI, Microsoft Research and Tesla.
Power
It was reported that xAI was incorporated in Nevada in June 2023 and Musk has purchased thousands of graphic processing units (GPUs) to power his AI vision. The company also has a Twitter account, @xAI, which has gained over 300,000 followers in less than a day.
Musk invited the public to ask questions about xAI on a Twitter Space – this was scheduled for 1h. July 2023. He has not provided any further details about the company’s mission, vision or products.
However, based on Musk’s previous comments and involvement in AI, it is likely that xAI will focus on developing artificial general intelligence (AGI), or human-level intelligence that can perform any task across any domain.
AI Critic
Musk has been a vocal critic of OpenAI, the AI research organization that he co-founded in 2015 but left in 2018. He has accused OpenAI of becoming too secretive, too commercial and too “woke”, especially after the launch of its popular chatbot ChatGPT.
Musk has also expressed his concerns about the potential dangers of AI, warning that it could pose an existential threat to humanity if not aligned with human values and goals. He has advocated for ethical and responsible development of AI, as well as global cooperation and regulation.
With xAI, Musk may be trying to create an alternative to OpenAI that is more aligned with his vision and values. He may also be aiming to achieve breakthroughs in AI that could benefit his other ventures, such as Tesla’s self-driving cars, SpaceX’s reusable rockets and Neuralink’s brain-computer interfaces.
However, xAI will also face many challenges and uncertainties in its quest to understand reality. AI is a complex and rapidly evolving field that requires massive amounts of data, computing power and talent. It also raises many ethical, social and philosophical questions that are not easy to answer.
Moreover, xAI will have to compete with other established and emerging players in the AI space, such as Google, Facebook, Amazon, IBM, Microsoft and Meta. These companies have invested billions of dollars in AI research and development and have access to vast amounts of data and resources.
It remains to be seen whether xAI will be able to achieve its ambitious goal and how it will impact the AI industry and society at large.
As Musk himself tweeted: “The future is weird.”
“Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks.”
AI race gathers momentum as China’s Baidu claims its Ernie Bot is Better than ChatGPT on key tests
Baidu said its AI system called Ernie 3.5 outperformed OpenAI’s ChatGPT and GPT4 in several key areas.
- The Chat Bot was revealed in March 2023 and has since been publicly testing it in China. The chatbot is based on Baidu’s foundational AI model called ERNIE.
- Baidu’s advancements underscore the intense competition taking place in the area of generative AI with technology giants in the US and China rapidly advancing their AI models.
ERNIE – Enhanced Language RepresentatioN with Informative Entities
Ernie was first introduced in 2019, and since then, Baidu has been improving and upgrading it with new versions. The latest version, Ernie 3.5, was announced in June 2023, and it claims to outperform OpenAI’s ChatGPT and GPT 4 in several key areas
Baidu’s Ernie is an artificial intelligence (AI) model that powers the company’s chatbot service, Ernie Bot. Ernie stands for Enhanced Language RepresentatioN with Informative Entities, and it is a natural language processing (NLP) deep-learning model that can understand and generate natural language.
Trained on large data sets
Ernie 3.5 is based on Baidu’s foundational AI model, which is trained on huge amounts of data from various domains, such as news, social media, encyclopedias, books, and more. Ernie 3.5 can handle various NLP tasks, such as question answering, dialogue generation, text summarization, sentiment analysis, and more.
According to a test by the China Science Daily journal, Ernie 3.5 surpassed ChatGPT and GPT 4 in general abilities and outperformed the more advanced GPT 4 on several Chinese-language capabilities.
ERNIE version 3.5 boosted its training and efficiency, making it faster and cheaper to upgrade to future versions. Baidu hopes that ERNIE Bot will become the next must-have app in China’s internet market, attracting users because of its natural and engaging conversations.
Intergration
Baidu has been integrating ERNIE Bot across multiple business applications, ranging from cloud computing to smart speakers.
ERNIE Bot is one of the examples of how Baidu is investing in AI technology and competing with other tech giants in the US and China. Baidu’s founder Robin Li, reportedly said that ‘foundation models are an engine driving global economic growth and represent a major strategic opportunity that cannot be missed‘.
The major BIG players, Alphabet (Google), Microsoft & META all have their own versions of AI. Hopefully it will be used ‘intelligently’.
What is AI?
AI stands for Artificial Intelligence, which is the ability of machines to perform tasks that normally require human intelligence. AI can involve various aspects of cognition, such as perceiving, reasoning, learning, problem-solving, and even creativity.
Types of AI
AI can be classified into different types based on the level of intelligence and the scope of tasks that machines can perform. One common way to categorise AI is by using the following four types:
- Narrow AI: This is the most common and basic type of AI, which refers to machines that can perform specific tasks very well, but cannot generalize to other domains or situations. Examples of narrow AI include speech recognition, face recognition, web search engines, recommendation systems, self-driving cars, and chess-playing programs.
- General AI: This is the type of AI that aims to achieve human-like intelligence across a wide range of domains and tasks. General AI would be able to understand and learn from any kind of data, reason and solve problems, communicate and interact with humans, and exhibit common sense and creativity. However, general AI does not exist yet, and it is considered a long-term goal of AI research.
- Super AI: This is the type of AI that would surpass human intelligence in all aspects, including speed, memory, knowledge, creativity, and wisdom. Super AI would be able to outperform humans in any task and domain, and potentially pose existential risks to humanity. Super AI is also a hypothetical concept that has not been achieved or proven yet.
- Artificial neural networks: This is a type of AI that mimics the structure and function of biological neural networks, which are the basis of human brain activity. Artificial neural networks consist of layers of interconnected nodes that process information and learn from data. Artificial neural networks are widely used for various applications of AI, such as computer vision, natural language processing, machine learning, and deep learning.
Applications of AI
AI has many applications in various fields and industries, such as:
- Healthcare: AI can help diagnose diseases, analyze medical images, design drugs, assist surgeries, monitor patients, and provide personalized care.
- Education: AI can help personalize learning, assess students’ progress, provide feedback, tutor students, grade assignments, and create educational content.
- Business: AI can help optimize operations, enhance customer service, automate tasks, analyze data, generate insights, improve decision making, and increase productivity.
- Entertainment: AI can help create music, art, games, movies, and other forms of entertainment.
- AI can also help recommend content to users based on their preferences and behaviour.
- Security: AI can help detect threats, prevent cyberattacks, enhance surveillance, identify frauds, enforce laws, and protect privacy.
- Social: AI can help communicate with humans through natural language processing and speech synthesis. AI can also help understand human emotions and behavior through sentiment analysis and facial expression recognition.
Challenges and limitations of AI
AI also faces many challenges and limitations that need to be addressed by researchers and users. Some of these include:
- Ethical: AI raises many ethical issues such as bias, fairness, accountability, transparency, privacy, human dignity, and social impact. How can we ensure that AI is aligned with human values and does not harm humans or society?
- Technical: AI still faces many technical challenges such as scalability, robustness, explainability, interpretability, generalization, and adversarial attacks. How can we improve the performance, reliability, and security of AI systems?
- Societal: AI also has many societal implications such as employment, education, regulation, governance, and collaboration. How can we adapt to the changes and opportunities that AI brings to our lives, work, and society?
AI is here to stay – it’s all about how we use it for the betterment of ‘humankind’. Please, let’s use it safely, responsibly and for the good!
Big tech companies heavily involved in the development of AI products
Alphabet/Google
Amazon
AMD
Meta