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 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.
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.
‘Well, what do you think of AI and cybersecurity sharing resources’? ‘Ha! playing right into our hands’.
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?
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.
U.S. restriction on AI related tech knowledge to China
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.
Gallium and Germanium considered critical elements required in the production of microchips
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.
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.
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.
‘Just checking the answer with my search engine!’
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, 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.
“Today we announce the formation of xAI,” the website states. “The goal of xAI is to understand the true nature of the universe.”
AI
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.
AI Robots at a bar
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.
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
US and China AI Bots go head to head
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.
AI Chatbot
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’.
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
