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Compared to chatgpt, DeepSeek: A Journey of Innovation and Growth

Mon, 24 Feb 2025 11:45:32 +0800

In the rapidly evolving landscape of technology and artificial intelligence, DeepSeek has emerged as a pioneering force, driving innovation and transforming industries. Since its inception, DeepSeek has been committed to pushing the boundaries of what is possible, leveraging cutting-edge technologies to solve complex problems and create value for its customers. This article delves into the founding of DeepSeek, its developmental milestones, and its current standing in the tech industry.

The Founding of DeepSeek

DeepSeek was founded in 2015 by a group of visionary entrepreneurs and technologists who shared a common goal: to harness the power of artificial intelligence (AI) and machine learning (ML) to address real-world challenges. The founders, each with a strong background in computer science, data analytics, and business, recognized the potential of AI to revolutionize industries and improve lives.

The idea for DeepSeek was born out of a series of discussions among the founders about the limitations of existing technologies in solving complex problems. They observed that while AI and ML were making significant strides, there was a gap in the market for a company that could seamlessly integrate these technologies into practical, scalable solutions. This realization led to the establishment of DeepSeek, with a mission to bridge this gap and deliver innovative AI-driven solutions.

Early Days and Initial Challenges

The early days of DeepSeek were marked by a combination of excitement and challenges. The founders were driven by a shared passion for technology and a belief in the transformative potential of AI. However, they also faced the daunting task of building a company from the ground up, with limited resources and a highly competitive market.

One of the first challenges DeepSeek encountered was attracting top talent. The founders knew that to succeed, they needed a team of highly skilled engineers, data scientists, and business professionals. They focused on creating a culture of innovation and collaboration, which helped them attract some of the brightest minds in the industry.

Another significant challenge was securing funding. In the early stages, DeepSeek relied on seed funding from the founders and a small group of angel investors. As the company began to demonstrate the potential of its technology, it was able to secure additional funding from venture capital firms. This funding was crucial in allowing DeepSeek to scale its operations and invest in research and development.

Key Milestones in DeepSeek's Development

Over the years, DeepSeek has achieved several key milestones that have shaped its growth and established its reputation as a leader in AI and ML. These milestones reflect the company's commitment to innovation, its ability to adapt to changing market dynamics, and its focus on delivering value to its customers.

1. Launch of the First AI-Powered Platform (2016)

In 2016, DeepSeek launched its first AI-powered platform, which was designed to help businesses automate and optimize their operations. The platform leveraged advanced ML algorithms to analyze large datasets and provide actionable insights. This launch marked a significant step forward for DeepSeek, as it demonstrated the practical applications of its technology and attracted its first major clients.

2. Expansion into New Markets (2017-2018)

Building on the success of its initial platform, DeepSeek began to expand into new markets and industries. The company developed specialized solutions for sectors such as healthcare, finance, and retail, each tailored to address the unique challenges of these industries. This expansion not only broadened DeepSeek's customer base but also reinforced its position as a versatile and innovative technology provider.

3. Strategic Partnerships and Collaborations (2019)

In 2019, DeepSeek entered into several strategic partnerships and collaborations with leading technology companies and academic institutions. These partnerships enabled DeepSeek to access new resources, share knowledge, and accelerate its research and development efforts. One notable collaboration was with a major university, where DeepSeek worked on developing advanced AI models for predictive analytics.

4. Introduction of DeepSeek's AIaaS (AI as a Service) Platform (2020)

In 2020, DeepSeek introduced its AIaaS platform, which allowed businesses to access AI and ML capabilities on a subscription basis. This platform democratized access to advanced AI technologies, enabling even small and medium-sized enterprises to leverage the power of AI. The AIaaS platform was a game-changer for DeepSeek, as it opened up new revenue streams and further solidified its market position.

5. Recognition and Awards (2021)

DeepSeek's innovative approach and impactful solutions have not gone unnoticed. In 2021, the company received several awards and accolades, including being named one of the "Top 10 AI Companies to Watch" by a leading technology publication. These recognitions served as a testament to DeepSeek's contributions to the field of AI and its commitment to excellence.

Current Development and Future Prospects

As of today, DeepSeek continues to thrive and innovate in the ever-changing tech landscape. The company has grown significantly since its founding, with a global presence and a diverse portfolio of products and services. DeepSeek's current focus is on advancing its AI and ML capabilities, exploring new applications, and expanding its reach into emerging markets.

1. Advancements in AI and ML

DeepSeek remains at the forefront of AI and ML research, continuously pushing the boundaries of what is possible. The company is investing heavily in developing more sophisticated algorithms, improving the accuracy and efficiency of its models, and exploring new areas such as natural language processing (NLP) and computer vision. These advancements are enabling DeepSeek to offer more powerful and versatile solutions to its customers.

2. Expansion into Emerging Markets

Recognizing the potential of emerging markets, DeepSeek is actively expanding its presence in regions such as Southeast Asia, Latin America, and Africa. These markets present unique opportunities and challenges, and DeepSeek is tailoring its solutions to meet the specific needs of businesses in these regions. This expansion is not only driving growth for DeepSeek but also contributing to the digital transformation of these economies.

3. Focus on Ethical AI

As AI technologies become more pervasive, there is a growing emphasis on ethical considerations and responsible AI practices. DeepSeek is committed to ensuring that its technologies are developed and deployed in a manner that is ethical, transparent, and fair. The company has established an AI ethics committee to oversee its practices and ensure that its solutions align with societal values and norms.

4. Future Prospects

Looking ahead, DeepSeek is poised for continued growth and success. The company is exploring new frontiers in AI, such as quantum computing and edge AI, which have the potential to revolutionize the industry. DeepSeek is also focused on fostering a culture of innovation and collaboration, both within the company and with external partners. By staying true to its mission and values, DeepSeek is well-positioned to remain a leader in the AI and ML space for years to come.

Conclusion at last

DeepSeek's journey from a fledgling startup to a global leader in AI and ML is a testament to the power of innovation, determination, and vision. The company's founders set out with a bold idea and a commitment to making a difference, and through their efforts, DeepSeek has transformed into a force to be reckoned with in the tech industry. As DeepSeek continues to evolve and expand, it remains dedicated to its mission of harnessing the power of AI to solve complex problems and create value for its customers. The future is bright for DeepSeek, and the world can expect to see even more groundbreaking innovations from this trailblazing company.

OpenAI CEO debuts new AI healthcare company: largely inspired by ChatGPT visits to the doctor

Tue, 16 Jul 2024 11:35:49 +0800

Last week, OpenAI CEO Sam Altman drew a lot of attention when he founded Thrive AI Health (Thrive), an artificial intelligence healthcare company. The company aims to address the chronic disease crisis plaguing 127 million people in the United States by changing patient behavior through AI health coaches, and has received an investment from America's richest man.

Healthcare has been a social issue of greater concern to American society and a key issue in this year's U.S. elections. An inefficient, high-priced healthcare system makes it difficult for many Americans to access effective care. As one of the top names in the AI industry today, Altman's choice to enter AI healthcare at this time has naturally raised many eyebrows.

The other founders who started Thirve with Altman are Arianna Huffington, founder of Thrive Global, a behavioral change technology company, and on July 11, they gave an interview to The Atlantic Monthly, revealing more details about the venture.

They said that Thrive will focus on providing health advice, avoiding medical diagnostic tasks that AI is currently not good at, and incorporating health information into future work scenarios.

However, when confronted with the interviewer's questions, they did not clearly explain what form the product will land in and what specific steps will be taken to ensure the safety of users' data.

Altman also said in an interview that "maybe" information between people and AI should be protected by confidentiality clauses between lawyers and clients, but he believes that this should be left up to society to decide.

It's worth noting that the AI health data obtained by Altman's new company, Thrive, is so private that it has significant economic value. Insurance companies could use this information to adjust the price of specific policies or decide whether to reimburse for a certain drug. The U.S. also recently experienced a breach of this information, which led to a massive healthcare system shutdown.

1. Focusing on health advice rather than medical diagnosis, the model performs "well enough"

The biggest selling point of Thrive, an AI health product, is that it's a "highly personalized AI health coach" that will provide personalized, instant health advice by collecting information about a user's sleep, food, exercise, stress, and social interactions, and combining it with expertise in the areas of medical records and behavioral change.

Altman and Huffington believe that AI health is important for improving the U.S.'s porous healthcare system. Currently, 90 percent of the cost of the U.S. health insurance system is spent on the treatment of chronic illnesses, and Thrive is expected to significantly reduce that cost.

Altman and Huffington compared the technology to Roosevelt's new policy, stating that "AI will be part of a more efficient healthcare infrastructure and continue to support people's health in their everyday lives."

However, the use of AI in healthcare is nothing new. AI has played an important role in areas such as CT reconstruction, drug development, and assisted diagnosis.

Currently, AI healthcare applications are mainly aimed at doctors and R&D personnel with specialized knowledge, rather than at patients with diseases in this campaign. Most patients do not have sufficient medical knowledge, so they are likely to be unable to make effective judgments about health advice or medical diagnoses made by AI, and it is difficult for AI products to ensure that they do not make mistakes.

Altman and Huffington responded to questions about the safety of the products in an interview with The Atlantic Monthly. They argue that the AI models are currently performing well enough. If Thrive focused only on "health advice" rather than "medical diagnosis" and utilized peer-reviewed data for training, the model could provide good enough advice.

However, neither Huffington nor Altman could give a clear response as to what form the product would ultimately take. They said the product will be launched as an app, but Huffington also said the product will be available through a variety of possible models, even similar to applications such as Microsoft Teams integrated into work scenarios.

2, Collecting data is not an issue. Altman said that users are willing to share

This hyper-personalized product will need to convince users to voluntarily transfer a lot of private information so that the AI can have enough information to make a decision. In an interview with The Atlantic Monthly, Altman argued that this is not a huge challenge.

Altman shared that part of the reason he started his new company is that many people have been diagnosed with medical issues with ChatGPT, and he's heard of many people trusting ChatGPT's advice to take the relevant tests and receive treatment. He believes that users are actually willing to share some very detailed and personal information with LLM.

The Atlantic Monthly reporter was very alarmed by this practice, as the medical advice returned by ChatGPT could have AI illusions and pose a threat to patients' health. Patients relying on this false information are also likely to have conflicts with specialized doctors.

The reporter also argued that once medical information is compromised, it could seriously jeopardize users' personal rights. But Altman was not firm in his reaction to the risk of information leakage, arguing that the issue should be handled by the community.

Communication between doctors, patients, lawyers, and clients is protected by law, and communication between people and AI should have similar protections, he says, "and maybe society decides whether to establish some form of AI privilege." In other words, they may not actively promote similar protections and leave the decision to society.

But protecting health data is imminent. As recently as February of this year, U.S. health tech giant Change, which is part of U.S. insurance and health group Healthcare, was hit by a massive ransomware attack that halted large-scale health insurance systems and put nearly one-third of Americans at risk of compromising their medical information.

Open AI has an imperfect resume when it comes to data protection.2023 Early in the year, Open AI's internal systems were subjected to a cyberattack that compromised the company's employee discussions and chats about advanced AI systems.

In addition, tech media outlet Engadget reported in early 2023 that ChatGPT had a serious information breach. At the time, ChatGPT's webpage experienced some glitches, which led to some users' conversation titles appearing in other chat boxes, and some users' identifying information and bank card details were leaked.

Nonetheless, Altman called on the community to give them "trust" in this interview, which is the exact opposite of his call for people not to trust him and OpenAI at the Bloomberg Technology Summit 2023.

Altman believes that there is a common expectation to improve the health of AI technology, which is one of the few application areas where AI can be utilized to change the world. He later added that in order to realize that AI improves human health, "a certain amount of faith is required," meaning that people have to believe that the new company can do this responsibly.

In the Times article, Altman and Huffington describe these "beliefs" in particular. They argue that to achieve "AI-driven behavioral change" and reverse the growing spread of chronic disease, they need three main areas of trust.

On the one hand, it comes from the belief of policymakers that they need to create a "regulatory environment that promotes AI innovation." Healthcare practitioners also need to trust AI tools and integrate AI technologies into their practices. Finally, individuals also need to trust AI to handle their private data responsibly. This is a really big ask for a business that doesn't have any products or promises to take any security measures.

Conclusion: handing over your health to AI may be early in the fashion, AI shouldn't be a faith game

When it comes to the implementation of AI health products, Altman and Huffington described the following scenario in Time: "An AI health coach would provide very accurate advice for everyone: replace your third soda of the afternoon with water and lemon; take a 10-minute walk with your kids at 3 p.m.:after school; start your relaxation routine at 10 p.m. " Artificial intelligence health coaches will eventually change some stubborn bad habits, ultimately improving the overall health of humans and extending their lifespan.

However, are the various "unhealthy" behaviors in people's lives a matter of personal habits or a broader societal problem? Should we leave the chronic disease crisis to individuals and AI solutions, or should it be systematically prevented through research and intervention by governments and healthcare organizations? These may be questions that people need to consider before the so-called AI healthcare infrastructure becomes a reality.

In the interview, Altman talks about how the realization of the AI health vision will require a certain amount of faith on people's part, but in far-reaching technological and healthcare fields such as AI, what we may really need is not such a faith game, but verifiable and explainable technology.

Musk says he will delay release of self-driving cabs due to changes to car's front design

Tue, 16 Jul 2024 11:32:25 +0800

Tesla CEO Elon Musk said Monday, July 16, that the company will need more time to release its self-driving cabs because it will need to change significant design changes to the front of the vehicle and show off other elements.

Though Musk did not reveal a specific date for the press conference. It was reported last week that the event, originally scheduled for Aug. 8, had been pushed back to October.

Musk responded to a user discussing the press conference event on his social media platform X: "I asked for a change in what I think is a very important design, and the extension will allow us to show other features."

A person familiar with the matter revealed on Friday that the self-driving cab press conference had been postponed, but did not provide further details.

Engineering and regulatory challenges abound in the development of self-driving cabs and autonomous driving systems. As a result, Wall Street analysts and Tesla investors believe the delay in the self-driving cab press conference is not surprising.

After reports surfaced on April 5 that Tesla had canceled its long-promised low-cost models, Musk announced that he would release the self-driving cabs in August and said the company would continue to develop them on the same small car platform.

So far, Musk has given few details about the self-driving cabs. He has only revealed that some vehicles will be owned and operated by Tesla, while others belong to individuals and can be rented out on Tesla's online platform. Tesla's stock market surged Monday after Musk publicly endorsed Donald Trump's bid for the U.S. presidency. Investors are hoping Trump will take office to help Tesla more easily get regulatory approval for self-driving cabs and systems.

Musk said in 2022 that Tesla expects to be able to mass-produce self-driving cabs without steering wheels or pedals by 2024, even though he's talked about achieving the goal of self-driving cars many times before.

Tesla shares rose 1.78 percent to close at $252.64 per share on Monday.

"Apple's replacement wave is underestimated"! Damo expects more than 500 million iPhone shipments in

Tue, 16 Jul 2024 11:25:35 +0800

AI technology is expected to stimulate the "new wave", institutions optimistic about Apple sales growth prospects.

Today's U.S. stock market before the plate, Apple shares rose more than 2%. On the news, Morgan Stanley rated Apple as a preferred stock, the target price was raised from $216 to $273, compared to last Friday's closing price is still 18.4% upside.

On Monday, JPMorgan analyst Erik Woodring issued a report saying that the Apple Intelligence feature will be a "notable catalyst" for a multi-year upgrade cycle for Apple devices, saying:

"We have previously underestimated the importance of the upcoming upgrade cycle, and the market continues to underestimate this at this time as well."

"We believe record levels of pent-up demand will be unleashed on the iPhone 16 range later this year, and at WWDC Apple debuted Apple Intelligence, reinforcing our belief that FY2025 could be the start of a multi-year device refresh cycle."

Benefiting from AI technology, Woodring expects Apple's average selling price (ASP) to grow at a 5% annualized rate, totaling $485 billion in revenue and $8.70 in earnings by fiscal 2026, beating consensus estimates by 7-9%, respectively.

Nearly 70% of shipments will be new models over the next two years

Morgan believes that the launch of Apple Intelligence technology will stimulate the potential "new" demand, thus starting a "multi-year upgrade cycle", driving shipments up strongly.

According to the report, since only the iPhone 15 Pro/Pro Max and newer models can support Apple's AI technology, it is expected to drive consumers to actively replace their iPhones with new ones, and promote the growth of iPhone ASP (average selling price).

Woodring forecasts that Apple will ship more than 500 million iPhones over the next two years, above the high 2021-2022 record. Shipments are expected to be 235 million units in fiscal 2025 and 262 million units in fiscal 2026.

Specifically, Big Mo expects 66-69% of iPhone shipments to be new models in FY25 and FY26, which is 2-6 percentage points higher than FY24 and 3 percentage points higher than the peak prior to FY22, driving annual iPhone ASP growth of 4-5%.

Woodring said that in addition to AI capabilities, the strong belief in the upgrade cycle is due to three factors that have never been seen before: an installed base of more than 1.3 billion devices, a longer upgrade cycle averaging 4.8 years, and the fact that newer technologies account for only 8% of the iPhone/iPad installed base.

Additionally, only 24% of iPads are currently supported to run Apple Intelligence, implying that the iPad is also likely to enter an upgrade cycle.

Just last week, Bank of America analysts Wamsi Mohan and others also issued a research report that expects generative AI to strengthen the willingness to replace iPhones with new ones this year, leading to strong sales growth and margin expansion, and raised Apple's price target from $230 to $256.

Apple launched Apple Intelligence function in June's WWDC, after the release of the company's shares once hit the first record high of the year, as of the close of trading on Friday, Apple's shares have accumulated 17%, more than the Nasdaq 100 index over the same period of 7% increase.

What is the Internet of Things? Internet of Things Overview and Detailed Explanation

Sun, 14 Jul 2024 17:55:38 +0800

What is the Internet of Things? Internet of Things? (Internet of Things, IoT) It refers to a networked system that connects a variety of physical devices, sensors, software, and other technologies over the Internet to enable them to communicate and exchange data with each other. Simply put, IoT is a technology that connects and controls a variety of physical devices over the Internet, enabling these devices to operate and interact automatically and intelligently.

The core concept of IoT is to connect and communicate with items in daily life (e.g., household appliances, automobiles, industrial equipment, etc.) via the Internet to achieve intelligent and automated control and management. Through embedded sensors, software and network connections, data can be collected, exchanged and analyzed to enable more efficient and smarter functions and services.

IoT has a wide range of applications covering home, city, industry, agriculture, healthcare and other fields. For example, smart home can realize remote lighting, temperature, security and other functions through IoT technology; smart city can optimize traffic management, environmental monitoring, energy use through IoT technology; industrial IoT can realize remote monitoring of equipment, predictive maintenance and other functions to improve productivity.

Internet of Things (IoT) It is a system of interconnected computing devices that can collect and transmit data over a wireless network without human input.

It's not just laptops and smartphones: almost anything with an on/off switch could be connected to the Internet and become part of the IoT. For example, a "thing" in the IoT could be a person wearing a heart-monitoring implant, a real-time camera transmitting wildlife in coastal waters, or a car with built-in sensors alerting drivers to potential risks. Essentially, any object that can be assigned an Internet Protocol (IP) address to transmit data over a network can form part of the IoT.

How does the IoT work? An IoT system consists of sensors/devices that communicate with the cloud through some form of connection. Once the data reaches the cloud, the software processes it and decides whether to perform an action, such as adjusting the sensor/device, without the need for user input or sending an alarm.

The complete IoT system has four distinct elements. Sensors or devices, connectivity, data processing, and user interface. Let's examine each one in turn:

Sensors/devices.

They collect data from their environment. The device may have multiple sensors, for example, a smartphone includes multiple sensors. GPS, camera, accelerometer, etc. Essentially, the sensor or sensors collect data from the environment for a specific purpose.

Connecting the

After the device collects data, it needs to send it to the cloud. It does this in different ways. - These include Wi-Fi, Bluetooth, satellite, Low Power Wide Area Network (LPWAN), or connecting directly to the Internet via Ethernet. Specific connection options will depend on the Ethernet. IoT applications.

Data Processing

Once the data reaches the cloud, the software will process it and may decide to perform actions. This may involve sending an alarm or automatically adjusting a sensor or device without user input. However, sometimes user input is required and this is where the user interface comes in.

User Interface

The user interface will enable this if user input is required or if the user wants to check the system. Any action performed by the user is sent through the system in the opposite direction. From the user interface to the cloud and back to the sensor/device change request.

The precise connectivity, networking and communication protocols used to support Web devices will be different for specific IoT applications. IoT is increasingly using Artificial Intelligence (AI) along with machine learning to make the data collection process easier and faster.

There are tons of IoT applications. Some of the most notable ones include:

Wearables.

Wearables are probably the most obvious aspect of the IoT for everyday users. These include fitness trackers, smartwatches, smart glasses, virtual reality headsets, and more.

Smart homes

Smart home systems connect with appliances to automate specific tasks, often remotely. Example IoT devices for smart homes may include wireless kitchen appliances, emotion-sensing music systems, smart lighting, motorized blinds, automated windows and doors, smart utility business instruments, etc.

Smart Cities

Smart cities use IoT devices such as connected sensors and instruments to collect and analyze data. This data can be used to improve infrastructure, utilities and services.

Self-driving cars

Self-driving cars usually have an IoT-based technology system that shares information about the vehicle itself and the road. Data on traffic, navigation, and the external environment is collected and analyzed by the car's computer system, enabling it to drive itself.

Retail

IoT is increasingly being used in retail. Consider, for example, automated checkouts, personalized discounts, smart shelves (which alert retailers when they are out of stock), robot employees and optimized supply chain management. Amazon Go-Amazon concept stores are an example of IoT bridging the gap between online and brick-and-mortar stores. These stores have no cash, as money is deducted from customers' Amazon wallets. They also add products to the customer's cart in real time as they pick them from the shelves.

Telemedicine

Telemedicine - sometimes referred to as telehealth - refers to the delivery of health services through technology. The Internet of Things is an important aspect of telemedicine (IoMT is sometimes used to refer to the Internet of Medical Things). Examples include telemedicine diagnostics, digital communications for medical imaging, and video consultations with specialists.

Smart Agriculture

Smart agriculture involves the use of digital technologies to improve agricultural work. For example, farmers can use connected sensors, cameras, and other devices to improve the overall view of the farm and adjust operations to improve yields.

This list is not exhaustive - there are many industries where IoT is transforming their operations and the way they work. Examples of IoT devices include smartphones, smart refrigerators, smartwatches, fitness trackers, smart fire alarms, smart door locks, smart bikes, medical sensors, fitness trackers, smart security systems, virtual assistants such as Alexa and Google Home - the list goes on.

The term "Internet of Things" in the history of the web is often attributed to Kevin Ashton. In 1999, Ashton was working on supply chain optimization at Proctor & Gamble and used the phrase as the title of a talk he gave on a new sensor project he was working on that caught people's attention. However, the Internet of Things predates this label: the

1970s: the idea of connecting devices was known at the time as "pervasive computing".

In the early 1980s, Carnegie Mellon University invented the world's first IoT device. A group of students created a way to ensure that their campus Coca-Cola vending machines reported their content over the Internet, saving them time from visiting the machines without a drink. They installed microswitches on the machines to report how many Coke cans were available and whether they were cold.

1990: John Romkey connects a toaster to the Internet for the first time.

1991:A group of students at Cambridge University used the first prototype webcam to monitor the amount of coffee available in a computer lab coffee pot. They did this by programming the webcam to take pictures of the coffee pot three times a minute. The camera sends the images to a local computer so that users can check whether coffee is available.

2000: LG Electronics introduced the world's first refrigerator connected to the Internet. This allows consumers to shop online and make video calls.

2008: The first international conference on the Internet of Things was held in Switzerland in 2008.

2010: The term IoT began to gain traction. As you know, Google's Street View service not only produces 360-degree images, but also stores data from people's Wi-Fi networks. It sparked a debate about whether Google planned to index not only the Internet, but the real world as well. That same year, the Chinese government announced that the Internet of Things would be the strategic focus of its five-year plan.

2011: Gartner, a market research firm, invented the New Technology Hype Cycle, which categorizes the Internet of Things as a new phenomenon.

2012: The theme of Le Web, Europe's largest web conference at the time, was "The Internet of Things". At the same time, more and more magazines, such as Forbes and Wired, started using IoT as part of their vocabulary.

2014: Google's announcement that it would acquire Nest for $3.2 billion brought IoT into the market consciousness. The Consumer Electronics Show was held in Las Vegas the same year. (CES) with IoT as the theme of the event.

Mid to late 2010s: During this period, devices with built-in Wi-Fi and 3G / connectivity to 4G were getting smaller, more powerful and cheaper to produce. This increased the spread of IoT.

It is estimated that by 2021 there will be more than 46 billion devices connected to the Internet of Things, and experts expect that by 2030 this number will increase to more than 100 billion.

IoT - Pros and Cons Observers claim that IoT has both pros and cons. This includes:

Network Advantage: Efficiency - Machine interaction increases the efficiency of machines, thus saving people time to focus on other tasks.

Automation - Automation leads to the harmonization of tasks and this improves the quality of service and reduces the need for human intervention.

Cost savings-Efficiency and automation reduce waste and labor costs, which in turn reduces the cost of producing and delivering goods.

Quality control - The Internet helps in better communication between equipment, which leads to better quality control.

Greater Transparency - The ability to access information on any device, anytime, anywhere can simplify decision making and lead to greater transparency.

Disadvantages of the Internet: Compatibility - Without internationally compatible standards, communication between devices from different manufacturers can be difficult.

Fewer jobs - With the accelerated automation of the IoT, it could replace skilled positions in the workplace.

Complexity - Given the sheer size of the IoT network and the many devices that depend on it, a single failure in software or hardware could have disproportionate consequences.

Privacy and security - Because so many everyday devices are connected to the Internet, there is a lot of information online. This creates privacy and security risks, which we will discuss in more detail below.

Some IoT privacy and security issues related to the IoT include:

Too much data-Networked devices can accumulate large amounts of data. It creates a possible entry point for hackers and makes sensitive information vulnerable to attack.

Vulnerability to hacking - For example, a group of researchers from Microsoft and the University of Michigan could find security holes in Samsung's smart home platform. Unwanted public personal information - Using an IoT device often involves accepting the terms of service, but many people don't bother reading lengthy documents and clicking accept. Companies collecting extensive information about users based on their IoT devices - For example, an insurance company might collect data about your driving habits based on your smart car when calculating life insurance. The same goes for fitness trackers. Eavesdropping - A manufacturer or hacker could use a connected device to eavesdrop on someone's home.

What does the future hold for the Internet of Things? A greater focus on security

Given the scale and complexity of the IoT, IoT devices may be vulnerable to cyberattacks and data breaches. The industry is taking this seriously and is working to provide better security for consumers. In the future, we will see more use of embedded and end-to-end security solutions, as well as AI, blockchain and edge computing solutions for IoT devices.

More IoT healthcare applications

After Covid, it's clear that IoT medical devices and IoT healthcare systems will play a more prominent role than ever before. For years, experts have been predicting an IoT revolution in healthcare, and the epidemic has accelerated progress. More and more medical appointments are being made through remote consultations. We can see the rise of IoT-based remote monitoring solutions and smart wearables, health trackers and sensors.

The rise of smart cities

In order to improve operational efficiency, share information with the public and provide better quality of government services and citizen welfare, cities around the world will increasingly look to smart technologies.

Artificial Intelligence and Machine Learning Will Become More Common

Artificial intelligence and machine learning will be the largest expenditure on IoT infrastructure in the coming years. The AI-powered IoT creates an intelligent machine that enables smart behavior and decision-making with little or no human interference.

5G networks will continue to drive growth growth

5G or fifth generation cellular wireless means faster speeds. Faster network speeds mean that data collected by IoT devices will be analyzed and managed on a wider scale. It may accelerate the growth of IoT. However, as more and more IoT devices with Wi-Fi routers connect directly to 5G networks, new privacy and security concerns will arise.

Enterprise IoT spending growth slows: to grow 12% to $301 billion this year, study says

Sun, 14 Jul 2024 17:38:42 +0800

　　Recently research firm IoT Analytics predicted that enterprise IoT sales growth will slow in 2024, continuing a downward trend from 2023 as economic uncertainty causes companies to scale back spending.

　　IoT Analytics said that enterprise IoT spending grew 15 percent year-over-year to $269 billion in 2023, but noted that this was lower than the 18 percent increase in 2022.

　　It forecasts a 12 percent increase this year to $301 billion, noting that there are signs of an upward trend in sales starting in 2025, with a projected compound annual growth rate of 15 percent from then through 2030.

　　IoT Analytics said that related services and hardware are "currently being hit the hardest" by a general slowdown in enterprise spending.

　　However, it predicted that spending will grow by 17% in China this year, with increases of 14% in India and 13% in the US. It predicts that over the next three to five years, these countries will remain at the forefront of the world.

　　The research firm predicts that spending by automakers will grow by 14 percent this year this year and 18 percent by 2025, due to "significant changes" in the automotive industry as electric vehicles become more prominent, as well as the need for "significant investments" in connectivity, real-time data processing and advanced driver-assistance system applications. "significant investment".

　　IoT Analytics explains that as automakers move from internal combustion engines to electricity, they "will have to re-engineer their entire factories."

　　Process manufacturing is also cited as a growth vertical, with spending expected to grow 13 percent in 2024 and continue to outpace the annual market average by up to 2 percentage points through 2030.

　　IoT Analytics lists operational efficiencies, safety improvements, and communication improvements as factors driving IoT spending among process manufacturers.

Current Development Status of Intelligent Driving

Sat, 13 Jul 2024 23:53:03 +0800

Intelligent driving is in a stage of rapid development and is gradually becoming a key growth point in the new energy vehicle industry. Advances in technology and policy support have accelerated the commercialization and application of intelligent driving. The penetration rate of intelligent driving is rapidly increasing, and although it still faces challenges in terms of safety and regulatory standards, with the continuous progress of technology and the improvement of the industrial chain, the development prospect of intelligent driving is very favorable. We can learn more about the current situation of intelligent driving from the following aspects:

Technological Progress

The progress of intelligent driving technology is mainly reflected in the maturity of the automatic driving system and the application of related technologies. Automatic driving technology is categorized into six levels from L0 to L5 according to the degree of automation, among which L4 and L5 levels are fully automated without human intervention. Currently, autonomous driving systems realize autonomous vehicle driving by sensing the surrounding environment and making driving decisions in real time. These systems rely on breakthroughs in cutting-edge technologies such as artificial intelligence, computer vision, LiDAR, millimeter-wave radar, high-precision maps and positioning technologies.

In addition, the application of 5G communication technology allows vehicles to exchange real-time information with other vehicles (V2V), infrastructure (V2I), and cloud servers (V2C), thus realizing real-time sharing of traffic information and intelligent traffic management. This technology can effectively improve the efficiency of traffic operation and reduce the rate of traffic accidents.

Policy Support

The United States is one of the earliest countries in the world to carry out automatic driving research and testing, with relatively complete construction of relevant regulations and standards, and leading automatic driving companies such as Google, Tesla, and General Motors. Germany, France, the UK, Sweden and other European countries have a strong foundation in the automotive industry and started earlier in terms of regulations and standards, providing a favorable policy environment for the application of intelligent driving technology. The Chinese government has always attached great importance to the development of intelligent connected vehicles, and has promoted technological innovation and industrialization in this field through a series of policies and plans. For example, policy documents such as the Outline for the Construction of a Stronger Transportation State and the Development Plan for a New Generation of Artificial Intelligence have planned the direction and goals for the development of intelligent connected vehicles. Recently, nine car companies have been authorized to enter the pilot program for access to and on-road passage of intelligent networked vehicles, which is a concrete manifestation of the policy support. The pilot program not only accelerates the maturity and application of the technology, but also provides a basis for the development of relevant laws, regulations and standards.

Market Prospects

The market share of smart connected cars is expanding, and it is expected that by 2030, the global smart connected car market size is expected to reach 1.5 trillion U.S. dollars. Intelligent connected vehicles can not only improve transportation efficiency and reduce traffic accidents, but also promote the development of related industries and create a large number of employment opportunities. In addition, the promotion of smart connected cars will also drive the development of intelligent transportation systems, smart cities and other related industries.

Challenges

Despite the broad prospects for the development of intelligent connected cars, they still face many challenges in the actual promotion process. First is the safety issue, the automatic driving system needs to maintain stability and safety in a variety of complex traffic environments, any small technical failure may lead to serious safety accidents. The second is the improvement of laws and regulations, at present, the relevant laws and regulations of intelligent networked vehicles are still imperfect, and it is necessary to summarize the experience and improve the legal system in the pilot process. The last is public acceptance and ethical issues, the public has doubts about the safety and reliability of self-driving cars, how to enhance public trust is an important challenge.

Future Development Trends

The development of intelligent networked vehicles will gradually move from the stage of technology verification to the stage of large-scale commercialization and application. In the future, with continuous technological advancement and sustained policy support, the market share of intelligent connected vehicles will continue to expand, with far-reaching impacts on the transportation system and urban management. The government will play a more important role in the development of intelligent connected vehicles, promoting technological innovation and application through policy guidance and financial support. The future transportation system will be smarter, safer and more efficient, the rate of traffic accidents will drop significantly, and traffic congestion will be effectively alleviated.

To summarize, intelligent driving technology is now developing rapidly and is strongly supported by policies. Despite some challenges, it has a promising future and is expected to achieve large-scale commercialized applications in the near future.

Main application directions of big models

Sat, 13 Jul 2024 23:46:50 +0800

Large models are machine learning models with huge parameter size and complexity. In the field of deep learning, it usually has millions to billions of parameters. Large models are closely related to artificial intelligence. Artificial intelligence aims to allow computers to simulate human intelligent behavior, covering a wide range of capabilities such as learning, reasoning, problem solving, etc., with a wide range of applications. And large models are an important part of the AI field.

Because of its huge number of parameters, big model has a powerful learning ability to learn complex relationships and patterns in the data, which is difficult to reach the traditional small model. At the same time, big models have better generalization capabilities and can perform well on unseen data. It can also be used for many different tasks, from language processing to image recognition.

As a kind of model based on large-scale pre-training, big model has shown its strong application potential in several fields. The following are the main application directions of big models:

Automated Driving

Big model brings a higher level of intelligence and more accurate decision-making ability in the field of automatic driving. It is capable of analyzing and interpreting sensor data to achieve real-time perception and understanding of the traffic environment, so as to accurately identify vehicles, pedestrians, road conditions, and so on. In addition, the big model can realize intelligent decision-making and planning based on deep and augmented learning technologies, such as path planning, lane keeping, and traffic signal recognition, to improve driving safety and efficiency1.

Multi-task Adaptability and Industry Convergence

The new paradigm led by big model technology is pushing AI toward "generalist" and accelerating its deep integration with various industries, giving rise to many innovative application scenarios. On the consumer side, office, picture generation and dialog products account for 60% of big model applications, and improving work efficiency has become the primary goal. And in terms of impact on various links in the enterprise value chain, they include R&D, manufacturing, operation management, marketing services and smart products2.

Weather Science Field

Breakthroughs have also been made in the application of big models in the field of weather science. For example, Google released GraphCast, a large model for weather forecasting based on graph neural networks, which predicts weather elements at different times and locations in the future by learning to extract relational features between nodes and atmospheric dynamics. The Pangu Weather Big Model, launched by Huawei Cloud's R&D team, on the other hand, has demonstrated accuracy in short- and medium-term weather forecasting that surpasses traditional numerical forecasting models2.

Robotics

Big models are also increasingly used in the field of robotics. For example, a U.S. robotics company, Figure, collaborated with OpenAI to integrate GPT-4 into robots to realize the control of robot actions and human-robot interactions by big models. This shows that big model technology is profoundly changing the robotics industry, making it more intelligent and flexible2.

Conclusion

To summarize, big models have a wide range of applications, from autonomous driving to weather science to robotics, big models are playing an important role, and with the continuous development of the technology, it may have more application scenarios in the future.

The first "laborers" whose jobs were taken by AI have already appeared

Fri, 12 Jul 2024 16:20:56 +0800

A recent event, ChatGPT took the jobs of 60 people. In the field of writing, retrieval and translation, it is not willing to be just a "small assistant". AI replacement for workers is no longer a "wolf", but really into reality.

BBC recently reported that ChatGPT replaced 60 employees of a technology company, the entire content team left only one person and ChatGPT. from now on, ChatGPT became the main author of the writing, another person is responsible for "touch-up". These 60+ workers were fired in less than a year from the time they joined the company.

What's going on here?

In 2023, writer Jamin Miller took a team of more than 60 people and contracted a tech company to promote its content. In Miller's eyes, it was a very fulfilling job. Until one day, the tech company decides to reduce operational costs and introduce automated systems. Miller's party A entered the headline into an online form that generated an article outline, and instead of having to conceptualize the article themselves, the editors under Miller wrote the article according to the generated outline. Miller, in turn, is responsible for the final review.

After a few months, the editors didn't even have to write the manuscript, switching to ChatGPT to do so. Most of the editors were fired, leaving a few to revise ChatGPT's copy to make it more humane. After some more time, by 2024, only Miller was left at Tech to revise the AI-generated articles. By this point, all 60+ editors had lost their jobs.

A situation like Miller's tech company is likely not an isolated case. Zooming out to the country's industries, the trend of AI replacing hitmen is also showing new signs. Recently, the U.S. media The Information released news that Apple has asked to cut assembly workers at its foundries in the next few years, with some product lines laying off half their staff.

Over the past year, Apple's vice president of operations has been working with foundries PEGATRON, Foxconn and Lucent Precision to spearhead the automation push. With the majority of iPhone shipments coming from China, this has had a knock-on effect on Chinese jobs. Apple has reportedly been trying to get rid of its reliance on Chinese workers, with workers in certain processes having been laid off by 30%.

Companies such as Apple and Tesla are supply chain weathervanes, and their moves have far-reaching implications for the manufacturing sector. China has always emphasized the importance of the real economy, and manufacturing is the key to the real economy. With the development of AI+Manufacturing, the jobs of hit workers are being adjusted by the impact, some may be on the verge of losing their jobs, and some are using AI to innovate their work methods to make their jobs smoother.

With the integration of ChatGPT, this in-car AI voice assistant has "captured" many European countri

Fri, 12 Jul 2024 16:16:11 +0800

SoundHound AI, Inc. the global leader in voice artificial intelligence (AI), delivered good news on Wednesday (10 EST), driving another collective high for AI concept stocks.

The company's SoundHound Chat AI voice assistant, which integrates ChatGPT, is now reportedly live and in production across Peugeot, Opel and Vauxhall car brands in 11 European markets, including Austria, France, Germany, Italy, Spain and the UK. By the end of July, the service will be available in 17 markets in 12 different languages.

Buoyed by the news, SoundHound shares surged more than 22 percent on Wednesday, hitting a new closing high since May 22nd. Other AI concept stocks also followed a rise: Baidu closed up 2.33%, C3.ai closed up nearly 1.8%, Oracle reversed the trend of decline rose about 1%, super micro computer rose nearly 0.5%.

At the same time, chip stocks also benefited from the rise. Philadelphia semiconductor index rose 2.42%, renewed record highs. Constituent stocks, Wolfspeed, Qorvo, ON Semiconductor, Si Jiaxun and Micron Technology rose more than 4%, the larger market capitalization of TSMC rose 3.54%, Asmax rose 3.68%, AMD rose 3.87%.

"Territory" expansion

It is understood that in March this year, Stellantis' DS Automobiles became the first automobile manufacturer to launch SoundHound Chat AI, which integrates the latest generative artificial intelligence technology, and DS Automobiles' cars have been launched in 18 countries and regions.

Stellantis is one of the world's top four carmakers and owns a number of well-known automotive brands. These brands include Abarth, Alfa Romeo, Chrysler, Citroen, Jeep, Lancia, Opel, Peugeot and Vauxhall.

Now, Stellantis is expanding its input to its Peugeot, Opel and Vauxhall brands to revolutionize the cockpit experience through interactive knowledge discovery, real-time data and effortless in-vehicle control.

According to a Stellantis press release, SoundHound Chat AI will be available in cars from these brands from this month. for certain previously released models, the carmaker will make it available on demand and can deliver it wirelessly without the need to visit a dealership.

SoundHound says that bringing SoundHound Chat AI to Peugeot, Opel and Vauxhall cars marks a new step in the company's mission to revolutionize in-car voice assistants.

The company's data shows a six-fold increase in the use of its voice assistant, DS Automobiles has reported a 50 percent increase in interaction frequency, a five-fold decrease in unfulfilled requests and a five-fold increase in net recommendations based on consumer loyalty, demonstrating the growing demand for sophisticated AI voice assistants from drivers and manufacturers.

What can AI voice assistants do?

It is understood that with the introduction of SoundHound Chat AI in Peugeot, Opel and Vauxhall, drivers and passengers will now enjoy a wide range of features with hands-free voice control. Whether it's managing navigation, making phone calls or accessing real-time information such as sports scores and weather updates, the voice assistant can enhance the convenience and enjoyment of driving.

ChatGPT's integration with Natural Speech Recognition is said to allow users to ask about any topic - from historical facts to creating stories for kids - to make the ride both informative and fun. For example, users can ask: "What is the most beautiful route from Paris to Bordeaux?" , "What are the historical places along the way?" , "How far am I from the first one?" , "What's the weather like there now?"

Once answered, users can also give direct commands, "Roll down the window and take me there." "Find the nearest electric car charging station." And so on.

Michael Zagorsek, COO of SoundHound AI, said, "Our partnership with Stellantis puts both companies at the forefront of innovation in the automotive industry, bringing the driving experience into an exciting new era.SoundHound is proud to offer voice AI technology that meets the market demand for next-generation consumer experiences built on natural conversations."