Last week, I discussed the dhistory and concepts of self-driving cars dating back centuries, with Leonardo da Vinci sketching a design for an automated vehicle in 1478. I then discussed progress made in self-driving, especially by Waymo and Tesla. This week I will explain the difference between self-driving and autonomous driving.
While the terms “self-driving” and “autonomous driving” are often used interchangeably, there are subtle but important differences in their meanings and implications. Self-Driving generally refers to vehicles which can operate without human input in specific conditions or scenarios. Self-driving may require human intervention or takeover in certain situations. It typically relies on a combination of sensors, cameras, and software to navigate pre-mapped routes.
Autonomous Driving implies a higher level of independence and decision-making capability. It refers to vehicles which can operate without any human intervention in all conditions. Autonomous driving uses advanced AI and machine learning to make real-time decisions and adapt to various environments.
A great example of autonomous operations was on display on Tuesday when SpaceX’s Crew Dragon space capsule brought astronauts home to Earth. When it was time to go, a SpaceX engineer or an astronaut pushed a button, and the SpaceX Crew Dragon space capsule took it from there. It undocked from the International Space Station, performed some tests, aligned itself properly and headed for Earth. When it was near Tallahassee, FL, two drogue parachutes were deployed to slow down the spacecraft. At a certain location and speed, the four main chutes were deployed and brought the spacecraft to a perfect splashdown landing in the Gulf of America off the coast of Florida. There was no human intervention.
It’s worth noting the terms self-driving and autonomous driving are not strictly defined and their usage can vary depending on the context and the speaker. For example, Tesla has been criticized for calling their cars’ feature an autopilot and then naming its capability Full Self Driving. Tesla has since renamed the capability as Full Self Driving (Supervised). The automotive industry is making a push toward using more precise terminology. Toward this end, the standards organization, SAE International, has defined six levels of driving automation, from Level 0 to Level 5.
Level 0: No Automation. The driver is in complete control of all vehicle functions. No manufacturers currently produce only Level 0 vehicles.
Level 1: Driver Assistance. The vehicle can assist with either steering or acceleration/deceleration. Most modern cars have some Level 1 features like cruise control.
Level 2: Partial Automation. The vehicle can control both steering and acceleration/deceleration simultaneously. The driver must remain alert and ready to take control at any time. Examples include Tesla’s Autopilot, Ford’s BlueCruise, and GM’s Super Cruise.
Level 3: Conditional Automation. The vehicle can drive itself under specific conditions, but the driver must be ready to take control when alerted. Mercedes-Benz has achieved Level 3 with its Drive Pilot system, limited to certain speeds and conditions. As of now, Mercedes-Benz’s Level 3 autonomous driving system is approved for use in only two states, Nevada and California. In California, Drive Pilot is approved for use in only specific areas: Bay Area, Central Valley, Los Angeles, Sacramento, San Diego, and on Interstate 15 connecting Southern California to Nevada. In Nevada, the system is approved for use along Interstate 15 from the California border to Las Vegas, on portions of highway in Las Vegas.
Even in these approved areas, the Mercedes system has operational limitations. It only works on pre-mapped freeways, it can only operate at speeds up to 40 mph, it functions only during daylight hours and requires specific traffic and weather conditions. Mercedes-Benz is currently the only automaker offering Level 3 autonomous vehicles for sale in the United States, but the limitations highlight Mercedes-Benz’s Level 3 technology is a significant advancement with significant limitations. Honda has announced plans for Level 3 technology with its Sensing 360 system beginning to roll out on certain models. They are projecting all models by 2030.
Level 4: High Automation. The vehicle can operate without human intervention in specific conditions or environments. As noted last week, Waymo is currently operating Level 4 autonomous taxis in select cities. Mercedes-Benz has gained approval to test Level 4 technology in Beijing. Toyota and Honda have announced plans to launch Level 4 services in Japan by 2024 and 2026, respectively. Tesla intends to roll out its first unsupervised rides using Full Self-Driving software in Austin, Texas, in June.
Level 5: Full Automation. The vehicle can operate autonomously in all conditions without any human intervention. No manufacturer has achieved Level 5 automation yet.
In summary, most major automakers are operating between Level 2 and Level 4, with Level 5 still being a future goal. Tesla, despite its “Full Self-Driving” name, remains at Level 2. Waymo leads in Level 4 deployment, while traditional automakers like Mercedes-Benz, Toyota, and Honda are making significant strides toward Level 3 and Level 4 automation. Exciting times ahead.
Read more about technology at johnpatrick.com.
In this section, I share what I am up to, pictures of the week, what is new in AI and crypto, and more.
My annual Tech Talk this year (#14) will be at 10am on March 27 in the Oceanview Ballroom at Hammock Dunes Club in Palm Coast. I will be talking about the latest with AI and Bitcoin. If you are in the area but not a member of the Club, let me know and I will be glad to add you to my guest list.
I will be speaking at the Senior Spectacular Expo in Ridgefield, CT on Saturday, April 26.
Heritage Hills in Somers, NY has invited me back for another talk on AI and Bitcoin. It will be on June 10.
Probus of Palm Coast was the first Probus social club in the U.S. There are approximately 4,500 Probus clubs worldwide with a total membership of around 300,000 people.
It was my honor to introduce the guest speaker, Shefiff Rick Staly. Sheriff Staly is serving his third 4-year term as Flagler County Sheriff. As Sheriff, he leads a workforce of more than 400 employees and volunteers with a budget of over $48 million dollars.
Sheriff Staly holds a master’s degree in Justice Administration from the University of Louisville and a bachelor’s degree in Criminal Justice from Rollins College. He also has had training by FBI and DHS. He is an impressive gentleman, and he gave an excellent talk. I was quite impressed with the depth of the Sheriff’s Office in AI, drones, and other technology.
Some statistics for 2024
Calls for Service; 111,635
Traffic Stops: 21,566Traffic Citations Issued: 5,994
DUI Arrests: 162
Crashes investigated: 1,673
Mirror on the lake at Hammock Dunes
At club. I don’t what it is but cool looking car.
David Sparks, also known as “MacSparky,” is a prominent figure in the Apple technology and productivity space. He’s a content creator, podcaster, blogger, and author who focuses on helping Apple users become more productive and efficient with their technology. I have been reading David’s writings for quite a few years. I always agree with him. The below is what he had to say about Apple Intelligence.
“For years now I’ve been writing and talking about the trouble with Siri. This problem became even more acute for Apple with the rise of large language models (LLMs) and the world’s collective realization at just how useful a smart artificial intelligence can be. Last June, it seemed as if Apple finally found religion about making Siri better. At WWDC 2024 they outlined the “Apple Intelligence” strategy that made a lot of sense. While I never expected Apple to build something on par with one of the frontier models, like ChatGPT, I continue to think they don’t need to. If Apple’s AI could remain private and access all my data, that alone makes it more useful than most artificial intelligence. Moreover, as the platform owner, a smart Siri could act as an AI traffic cop, sending more complex requests to the appropriate outside models.
So I think Apple has the right vision, but I’m starting to question their ability to execute on it. Apple has yet to release even a beta of the iOS 18 version with, as one Apple employee explained to me, the “Siri Brain Transplant.” Indeed, Apple recently announced that the advanced Siri features won’t ship in iOS 18 after all. So the brain transplant has been postponed.
Late last year, there was a rumor that Apple is working separately on an LLM-Siri for iOS 19 that will really show how good Siri can be. The fact that there is already a rumor of a new thing when we don’t yet have the improved old thing doesn’t inspire confidence.
It gets worse, though. Mark Gurman, a reliable source, now reports the new LLM Siri is also behind and its conversational features may not release to consumers until 2027. Ugh. If true, Apple’s failure to deliver on Siri is epic at the Apple Maps and MobileMe launch levels.
The current LLM leaders are evolving weekly. Can you imagine how good they are going to be by 2027? I honestly can’t.
If these rumors are true, Apple is in trouble. It’s not the 1995 Apple-will-they-go-out-of-business-trouble, but it is trouble nonetheless. M.G. Siegler suggests that if Apple truly is this far behind, they should just default to ChatGPT until they can get their act together. That would be incredibly embarrassing for Apple, but this whole situation is exactly that. It looks like Apple’s AI initiative has a long way to go. Back in the day when the MobilMe launch failed so miserably, people joked that Steve Jobs was walking through the hallways at Cupertino with a flame thrower strapped to his back asking everyone he met, “Do you work on MobileMe?”. When it comes to AI, I think Apple is approaching a flame thrower moment.”
Several significant developments have occurred in the AI world this week:
Nvidia’s GTC 2025 Conference
At the GTC 2025 conference on March 18, Nvidia’s CEO Jensen Huang unveiled the company’s next-generation graphics architectures. The Blackwell Ultra chip is set for release in the second half of 2025, followed by the Vera Rubin AI chip in late 2026. Huang projected that Nvidia’s data center infrastructure revenue could reach $1 trillion by 2028, driven by surging demand for GPUs from major cloud service providers[2].
OpenAI’s Upcoming Model Releases
OpenAI is reportedly on the verge of releasing significant updates to its AI models. GPT-4.5 is expected imminently, with the more substantial GPT-5 model potentially arriving as early as May 2025. The upcoming GPT-5 model will integrate the o3 reasoning system to enhance fact-checking capabilities[2].
Google’s AI Strategy
Google is positioning artificial intelligence at the center of its strategy for 2025. The company plans to expand its Gemini AI model to power multiple products and services, including search, personal assistants, and enterprise solutions. Google is focusing on enhancing its search capabilities to counter emerging competition from AI-driven rivals like OpenAI and Perplexity[2].
Embodied AI Advancements in China
China is making significant progress in embodied AI development, which integrates AI into physical bodies such as robots. Many cities are funding projects to advance embodied intelligence systems, allowing AI to physically interact with the world. The Guangdong-Hong Kong-Macao Greater Bay Area is emerging as a hub for humanoid robot development[3].
Debate on Artificial General Intelligence (AGI)
As AI models become increasingly capable, the debate around artificial general intelligence (AGI) continues. Researchers are developing benchmark tests to evaluate how close systems are to achieving AGI. However, experts remain divided on the definition and practical utility of AGI, with some arguing that it functions more as a marketing term than a concrete goal[4].
Mendix 10.18 Release
Mendix has released version 10.18 of its platform, addressing AI development challenges with new features and enhancements. The update includes AI-powered assistance across the entire software development lifecycle, simplified onboarding, and improved accessibility and governance around GenAI output and environments[5].
These developments reflect the ongoing advancements and debates in the AI industry, with a focus on more powerful hardware, improved language models, and the integration of AI into various applications and physical systems.
Several significant developments have occurred in the crypto world this week:
Federal Reserve Decision Impact
The Federal Reserve’s decision to maintain interest rates at 4.25%-4.50% has sparked a rally in the crypto market. Bitcoin surged above $85,000, reaching $85,786, while Ethereum climbed to $2,022[5]. This decision has shifted market sentiment, with the Crypto Fear and Greed Index moving from “Fear” to “Neutral” territory[5].
Institutional Interest Growing
A survey by Coinbase and EY-Parthenon revealed that 83% of institutional investors plan to increase their crypto allocations in 2025. Nearly three-quarters of firms surveyed already hold cryptocurrencies beyond Bitcoin and Ethereum, with XRP and Solana being the most popular altcoin holdings[3].
Altcoin ETFs and Futures
The crypto market is anticipating the launch of Solana exchange-traded funds on March 20, 2025. This follows the Chicago Mercantile Exchange Group’s introduction of Solana futures contracts on March 17, marking a significant step towards institutional adoption of altcoins[3].
Trump’s Crypto Policy Announcement
President Donald Trump is expected to make a major crypto policy announcement at the Digital Asset Summit in New York. This will make him the first sitting U.S. president to address a crypto conference, potentially signaling important developments in U.S. crypto regulations[7].
Trust Wallet Dominance
Trust Wallet has become the most downloaded crypto wallet globally in March 2025, capturing over 35% market share. The wallet’s success is attributed to its user-friendly interface, support for multiple blockchain ecosystems, and enhanced security features[8].
Emerging Cryptocurrencies
New cryptocurrencies like Qubetics ($TICS) are gaining attention. Qubetics is currently in its 26th presale stage, having raised $15.2 million so far. Analysts predict its token price could reach $0.25 by the end of the presale[2].
These developments reflect the ongoing maturation and mainstream adoption of the crypto market, with increasing institutional involvement and regulatory attention shaping the industry’s future.
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