He stated he’s pursuing this project because semiconductor manufacturers are not producing chips fast enough to meet his companies’ AI and robotics demands. Musk said:

“We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab.”

According to Bloomberg Musk shared his plans during an event in downtown Austin, Texas, with a photo indicating that the “Terafab” facility will be “gigafactory,” located near Tesla’s Austin headquarters.

He also added that the aim is to produce chips capable of supporting 100–200 gigawatts of computing power annually on Earth, as well as one terawatt in space. He did not provide a timeline for the plan.

Image: Presentation of the Terafab project

Having operated in the city for years, Waymo has been methodically expanding its services. The company now facilitates tens of thousands of weekly trips, offering a safe, sustainable, and reliable transportation option for the local community and tourists alike.

Strengthening Community Ties

Waymo is becoming integral to San Francisco’s urban fabric. According to the company, 30% of its rides are directed to local businesses, boosting foot traffic to restaurants, music venues, coffee shops, and more. A recent survey highlighted that over half of Waymo’s users have utilized the service for medical appointments, while 36% connect to other transit systems such as BART or Muni. The service is even popular for wedding departures, adding a touch of modernity to traditional ceremonies.

“I’m thankful to be living in a city that embraces technology when it can improve our lives with convenient and safe modes of transit,” said Michelle Cusano, Executive Director at The Richmond Neighborhood Center.

Committing to Sustainability

In line with San Francisco’s environmental goals, Waymo’s fleet is entirely electric and powered by 100% renewable energy from the City’s CleanPowerSF program. Since its commercial launch in August 2023, Waymo has reduced carbon emissions by an estimated 570,000 kg. Survey results indicate that 53% of users feel that using Waymo has helped them adopt more environmentally friendly travel habits.

Enhancing Safety and Inclusivity

Safety remains a top priority for Waymo. More than half of its riders in San Francisco report an increased sense of personal safety when using the service. Charles Renfroe, Development Manager at Openhouse SF, praised the service for providing a harassment-free travel experience for transgender and gender non-conforming individuals.

Waymo also caters to tourists, with many enjoying rides to landmarks like the Presidio and the Ferry Building. The app supports Spanish and Chinese languages, ensuring accessibility for a diverse user base.

Milestones and Impact

Since Waymo’s waitlist opened, nearly 300,000 people have signed up for the service. With over 20 million rider-only miles and nearly 2 million paid trips, Waymo has demonstrated a strong commitment to safety. Data shows that Waymo’s autonomous vehicles are involved in fewer collisions and insurance claims compared to human-driven vehicles.

Addressing Road Safety

Waymo’s technology aims to enhance road safety, a pressing issue in San Francisco where traffic accidents remain a serious concern. The Waymo Driver is designed to avoid high-severity collisions more effectively than human drivers. Patricia Rillera, Executive Director of MADD California, highlighted the potential of autonomous vehicles to reduce accidents caused by impaired driving.

Community Engagement and Innovation

Waymo collaborates closely with city officials, first responders, and road safety advocates to ensure its service benefits the community. The company is committed to providing safe, eco-friendly transportation options that positively impact local mobility.

Waymo extends its gratitude to its riders, community partners, and the residents of San Francisco for their support. Together, they are helping to keep the city at the forefront of technological innovation, offering a safe, clean, and enjoyable transportation experience for all.

AutoSens Awards originate from 2015. Since then, they have been selecting the most innovative companies and products leading the global autonomous driving industry. This year, StradVision won the Gold Award in ‘Best in Class Software for Perception Systems‘ for its self-developed deep learning-based camera perception software SVNet, at the virtual awards ceremony held on November 24th. Junhwan Kim, CEO of StradVision, commented:

“I am very excited to win one of the most prestigious awards in the autonomous driving industry. StradVision is striving to provide camera perception solutions that achieve the best performance and the highest efficiency. We’ll keep moving forward to spur technology development and business expansion, so the benefits of ADAS and autonomous driving solutions will be accessible to all drivers and pedestrians.”

SVNet is а state-of-the-art perception software that supports ADAS features of driving automation levels 2 and 3 and 4. The software delivers unmatched high performance and efficiency that enables cutting-edge deep learning-based camera perception with minimal computation and power consumption.

What is more, SVNet provides over 30 features for recognition of road environments such as other vehicles, pedestrians, traffic lights and signs, and animal detection. It offers high compatibility for 14 different SoC platforms and enables surround vision systems by integration with multiple sensors such as LiDAR and RADAR.

StradVision was established in 2014, and has been leading the development of autonomous driving technology via its AI-based vision perception software. The SVNet software is currently being deployed in over 50 vehicle models from 13 OEMs worldwide.

Photo Credits: StradVision

In terms of dealer’s income, the market grew by approximately 20.6 per cent, year-over-year, in Australia and almost 20.4 per cent, year-over-year, in New Zealand during the first half of this year.

As the pandemic forced us to remote work, the collaboration applications segment has led the charge, claiming the greatest annual growth rate of the entire software market,  reaching around US$257.8 million across A/NZ.

According to IDC, businesses continue to invest in team collaborative applications in order to support productivity, effective communications with clients and partners, and promote engagement among employees in a new hybrid environment.

At the same time, a huge number of organisations are launching their digitisation journeys and influencing digital technologies.

Artificial intelligence platforms showed the second strongest year-over-year increase of any segment in the software market, after collaboration apps, growing by almost 35 %across A/NZ and reaching  approximately US$111.5 million. This rapid growth means strong demand from A/NZ organisations in modernisation and the streamlining of core business processes, according to the analyst firm.

Moreover, the fulfilment of AI software services and intelligent knowledge discovery tools is on the rise, supporting decision-making and forecasting, and improving business outcomes.

According to Anastasia Antonova, who is a senior market analyst at IDC A/NZ, organisations across Tasman are investing in intelligent process automation tools and leveraging AI capabilities. In that way, they modify operational processes and improve customer and business data analysis in their collective bid to meet individual customer needs.

The third strongest annual growth during this period of time is about 31%, reaching approximately US$164.6 million and it belongs to the integration and orchestration middleware software. The rapid growth of integration software has been largely driven by legacy modernisation, hybrid integration, workflow and process automation and application programming interface (API)-led innovation initiatives, according to IDC.

Research by Gartner,suggested that global AI software spending will grow roughly 21.3% to about US$62 billion during the next year.

The analyst firm indicated that knowledge management, virtual assistants, autonomous vehicles, digital workplace and crowdsourced data would make up the top five use cases for AI software spending in 2022. Gartner senior research director Alys Woodward said:

“Use cases that deliver significant business value, yet can be scaled to reduce risk, are critical to demonstrate the impact of AI investment to business stakeholders.”

The report also noted that the demand for AI technologies and associated market growth is closely tied to organisational AI maturity levels.

The sector will have had a revenue boost of 21.3% compared to this year if it manages to reach that number. According to Gartner’s analysis, AI software included categories such as Knowledge Management, Virtual Assistants, Autonomous Vehicles, Digital Workplace, Crowdsourced Data, and Others.

Amongst the categories mentioned above, Knowledge Management is expected to see the strongest growth next year at 31.5% and Virtual Assistants will see the least growth at 14.7%. According to the analyst firm, however, it could take until the middle of the decade before half of organisations worldwide adopt AI in a more mainstream fashion which it called the ‘stabilisation stage’ of AI maturity. Commenting on the findings, Alys Woodward, senior research director at Gartner, said:

“The AI software market is picking up speed, but its long-term trajectory will depend on enterprises advancing their AI maturity. Successful AI business outcomes will depend on the careful selection of use cases. Use cases that deliver significant business value, yet can be scaled to reduce risk, are critical to demonstrate the impact of AI investment to business stakeholders.”

Gartner said that AI will continue to increase as organisations and will probably overcome their reluctance to embrace and trust AI, and find ways to deliver business value from AI technologies.

“In a nutshell, MobileCharger is a mobile power bank for autonomous robots. Can you imagine that soon thousands of delivery robots will travel through the city next to us? If one or several such robots are discharged, it will be a serious obstacle for pedestrians and traffic.”

The general idea behind the recent study by Tsetserukou and his colleagues was to devise a system that can reach faulty robots or robots with depleted battery power and assist them. The system they developed, dubbed MobileCharger, can charge robots as they are operating and trying to complete a mission, such as delivering a parcel or collecting data in a specific location. Tsetserukou also explained:

“A delivery robot and MobileCharger can run as one unit until the target robot is fully charged. Subsequently, MobileCharger detaches and goes to a new robot or charging station.”

Aerial refuelling allows aircraft to remain in the air longer and can lead to 35–40% fuel savings during long-range missions. The system devised by Tsetserukou and his colleagues may thus be highly valuable, as the deployment of several of these systems as a swarm could decrease the costs of robot missions and shorten the time a delivery robot takes to deliver items to a given location. Tsetserukou also added:

“Instead of losing time for travelling to the charging station, delivery robots can always be engaged in the mission. In the future, it will be also possible to create a MobileCharger energy harvester with an integrated solar panel. This would mean that when the battery is near exhausted, a robot can simply move to a sunny spot and position solar panel towards sunlight.”

Video of DeltaCharger, Credit: Okunevich et al.

MobileCharger is the first robot that can directly charge other autonomous robots on the go. Its most characterizing component is the DeltaCharger, a system that can position electrodes in three dimensions (3D) to sustain charging in situations where a target robot is not horizontally or vertically aligned to the charger. This could happen, for instance, when a robot is running over stones and other objects or when a robot’s configuration does not allow it to be favourably positioned for charging. Tsetserukou explained:

“Computer vision systems are not as effective as tactile ones in detecting the electrode misalignment in close proximity. DeltaCharger has an advanced tactile perception, as it is based on high-density pressure sensors provided by Professor Hiroyuki Kajimoto from the University of Electro-Communications in Tokyo, Japan.”

Tsetserukou and his colleagues also developed a convolutional neural network (CNN) that can evaluate the angle of misalignment between the electrodes on MobileCharger and those on a robot that requires charging. This algorithm was trained on a series of tactile patterns comprised of 100 points.

The team evaluated the CNN in a series of tests and found that it could measure the angle, vertical and horizontal values of electrode misalignment by analyzing pressure data with remarkable accuracies of 95.46%, 98.2%, and 86.9%, respectively. This means that the robot charging system they developed should be able to attach itself to a variety of robots with different configurations, irrespective of the environment they are in when they need charging. Tsetserukou noted:

“Besides the charging of mobile robots, a future application of the technology may be the charging of drones in midair, with a charging drone based on the DeltaCharger mechanism wired to the ground power station and a target UAV being recharged without landing. Innovative autonomous ships and tankers with electric motors could also be charged during sailing with the proposed concept, as this would prevent them from having to enter ports for refuelling. Additionally, any types of robots such as robot dogs, outdoor cleaning robots, and even self-driving cars can be charged in a similar way.”

In the future, the innovative robot charging system developed by this team of researchers could be adapted to charge countless different robotic systems, ranging from autonomous vehicles to mobile robots. Meanwhile, Tsetserukou and his colleagues plan to continue working on the initial prototype they created to further improve its performance and generalizability.

Apple has been working on the ultimate garage product for years. We’ve never seen it, but the company apparently has thousands working on it, has invested hundreds of millions of dollars in the effort, and some form of vehicle is expected in the next few years. According to the Morgan Stanley analyst Katy Huberty:

“In any new product category, there are other technology companies that are happy to bring a product to a market that maybe isn’t the prime time or a product that isn’t perceived to be perfect. Apple takes the other side of that. The strategy is about doing fewer things, but doing them really well, and increasing the chances of success.”

It remains possible Apple could abandon such plans because the challenges it is trying to solve are evolving rapidly. At the same time, the auto industry has begun a deep and unavoidable transformation in which its entire reason to exist must change. Before considering Apple’s approach, it’s important to consider the bigger picture of vehicle manufacturing.

Everything is being disrupted:

• Climate change means the industry has no choice but to abandon fossil fuels. A move to electronic vehicles in Beijing, for example, would make the city 2 degrees Fahrenheit cooler, though the overall benefits remain a little unclear.
• Replacing all existing vehicles is not an option, due to the need to preserve raw materials and the pollution created in manufacturing them.
• The cost of maintaining vehicles will grow. Some existing suppliers may not make the transition, and we’re also looking at fast-paced regulatory change.
• Autonomous vehicle development is hard. And as cars become autonomous, what we do inside them will also change.

Changing gears

It’s becoming more widely understood that all these changes will mean an initial increase in Electric Vehicles (EVs), followed by the emergence of truly Autonomous Vehicles (AVs). This transition will likely be accompanied by an increase in public transit and micro-mobility solutions, such as electronic scooters, autonomous transit systems, bicycles and so on.

City planners in some nations are attempting to nurture the use of personal transportation in this way by making it costlier and less efficient to take short journeys by car.

What this means is that many will find fewer reasons to need a car, the number of cars sold will shrink, and the reasons for owning a vehicle will change. Auto manufacturers know this, which is why many are investing in EV development, charging technologies and ride-sharing schemes.

Before it enters this space, Apple must try to answer the same questions every existing manufacturer is attempting to solve:

• How big is the auto market going to become?
• What will it be?
• What will cars become?
• What will we expect of them?
• And what about vehicle ownership?
• As the notion of public transport extends to include car and ride sharing, what will the high-end market demand?

Apple’s answer will be services

Huberty also noted:

“Apple is successful when they’re vertically integrated. They want a hand in the design, in how the software communicates with the hardware, what are the right components and technologies to use…. Apple will just as much focus on the other elements — building, designing, what that vehicle looks like, how the components and the software operate together—as it will on the services.”

The first part of Apple’s road trip, then, will be about getting its vehicles out there leveraging the design and consumer trust, with the services component — and inevitable developer platform — set to follow. You can see this model in iPod, iTunes, iPhone, and the evolution of the App Store, which turned iPhones into anything you need them to be.

What’s the business plan?

It seems safe to assume Apple will attempt to build an outstanding core product that is supplemented by a range of profitable services and accessories. So what can Apple build beyond that and where can it define margins?

Let’s begin with a touch of luxury. Anyone who has ever seen the Apple Watch strap display in-store will recognize the company dabbles in luxury.

That means part of Apple’s proposal will likely be various build-to-order and aftermarket vehicle upgrades: Seats and interiors, battery size, wheel trim and more. There are plenty of vehicle manufacturers who generate plenty of revenue with accessories and upgrades. Beyond the physical stuff, what services might be required in cars that eventually become autonomous?

Here are six ideas:

• I imagine part of Apple’s plan may emulate the economics of radio, so location-based ads, offers, and Maps-related technologies may sit around an in-car entertainment service. This also explains Apple’s own radio stations, its limited support for stations from outside its walled garden, and current investments in podcasts.
• The Apple Car Care service will be popular. I imagine this will provide subsidized repair, maintenance, and emergency services during the life of the vehicle for an annual fee.
• Owners who choose to enrol their vehicles in the Apple Car Share scheme to make a little money when their car is otherwise stationary will give Apple 15%-30% of the proceeds.
• Core software upgrades are likely to be made available for free, with additional functionalities made available as paid-for downloads.
• That’s also where the heavily vetted App Store may sit.
• Apple’s determination to create a closed-loop manufacturing system and its commitment to zero emissions means any vehicles it does put on the road will also see it make an additional direct and indirect local investment in clean energy supply.

But before it makes money on any of these services, Apple must get the car right – and this may turn out to be an incremental journey. Huberty commented:

“I wouldn’t be surprised if Apple comes to market with an EV, right? A car that looks similar to automobiles that are on the market today with a steering wheel.”

How do you differentiate on the hardware?

That’s something Apple’s teams have been working on for a while, with Apple already owning patents for hazard detection, AR windshields, suspension and braking systems, climate control and more.

Spartan Radar builds cutting-edge software that improves radar performance for use in autonomous vehicles, making radar competitive with lidar, which has traditionally been used by auto manufacturers in self-driving vehicle applications. Spartan’s Biomimetic Radar™ mimics human perception processes for enhanced focus and context; proprietary algorithms dramatically speed up processing and reduce radar’s historic shortcomings, including lower resolution and false detections. Their software is almost entirely hardware agnostic and can be deployed on existing radar systems, potentially even in cars already on the road as an over-the-air system update. Spartan Radar Founder and CEO Nathan Mintz said:

“The automotive industry’s pivot to lower levels of automation makes radar more attractive than lidar. While showing lots of initial promise, lidar is failing to live up to all the hype, but the need for high resolution systems hasn’t gone away. The processing power finally exists to utilize advanced algorithms like super-resolution in real time to make radar a far better option for automakers.”

The funding will help Spartan scale its engineering team, build a full-scale prototype, conduct field tests, and acquire a greater share of the more than $32 billion advanced driver assistance systems (ADAS) market, which is expected to reach $142 billion by 2027, according to Precedence Research. Suzanne Fletcher, General Partner at Prime Movers Lab, which invested in Mintz’s previous company Epirus said:

“What sets Spartan apart is its deep technical team of industry experts. There are only a few CEOs out there who can build two startups that redefine their industries, and we believe Nathan is one of those founders. The Spartan team’s deep experience with military radar will help them create cutting-edge improvements to autonomous vehicle applications.”

Spartan was founded in 2020 by Mintz, Chief Revenue Officer Blake Gasca, Dr. Theagenis Abatzoglou, Dr. Joe Zhou, and Chief Technology Officer Tyler Rather.

DeepMap’s technology will bolster the mapping and localization capabilities of NVIDIA DRIVE after the acquisition is expected to close in the third calendar quarter of 2021. According to Ali Kani, vice president and general manager of Automotive at NVIDIA:

“The acquisition is an endorsement of DeepMap’s unique vision, technology and people. DeepMap is expected to extend our mapping products, help us scale worldwide map operations and expand our full self-driving expertise.”

The latest release of Visual Studio Code 1.57 includes updates such as Workspace Trust, a new getting started experience, remote repositories and much more.

Workspace Trust lets users decide whether their project folders should allow or restrict automatic code execution and enables safe code browsing. What is more, the new Edge browser debugging feature integrates the Microsoft Edge Developer tools directly into VS Code.

• The new FIDO Developer Challenge invites teams to use the public FIDO2 WebAuthn API to showcase unique FIDO authentication ideas.

The FIDO Alliance stated that the projects should apply FIDO authentication protocols to address technical or social challenges within Fintech, eCommerce, IoT, retail, blockchain, gaming and education. The deadline for entry is July 2nd.

• The new Powered by Snowflake program is specifically designed to accelerate the ability of companies and application developers to deliver differentiated applications through all stages of the application in Snowflake’s Data Cloud.

The program will allow users to build better applications with faster engineering velocity by leveraging Snowflake design resources and will also drive awareness and adoption by co-marketing with Snowflake.

Those who participate in the program will also be able to optimize performance by working with support engineers who specialize in app development.

• The new version of TMS WEB Core includes package support to easily create custom components, Workspaces that allow users to manage multiple projects in one folder, and support for the use of the entire FNC component suite.

Using TMS WEB Core, modern client-side web applications can be created exclusively with the Object Pascal programming language without the need for HTML, CSS or JavaScript.

All new components and improvements are now available to Visual Studio Code users.

Bakur Kvezereli did. Raised on an Eastern European organic tomato farm, he saw labor shortages, pesticide problems and rising energy costs. Years later, studying at MIT in 2014, it dawned on him that AI could help address these issues for farmers.

A few years later, he founded Ztractor, an autonomous electric tractor startup based in Palo Alto, Calif.

Ztractor offers tractors that can be configured to work on 135 different types of crops. They rely on the NVIDIA Jetson edge AI platform for computer vision tasks to help farms improve plant conditions, increase crop yields and achieve higher efficiency.

Going electric means Ztractor machines also don’t belch out plumes of black diesel exhaust.

The company is among a growing field of agriculture companies like Bilberry, FarmWise, SeeTree, Smart Ag and John Deere-owned Blue River adopting NVIDIA GPUs for training and inference.

AI Supports Organic Farms

In many countries, farm labor is limited. A survey by the California Farm Bureau Federation reported that 56 percent of more than 1,000 farmers were unable to hire adequate labor.

ZTractor offers three different models to help assist farmers. Each sports 67 sensors, six cameras and GPS. The tractors collect field data that’s fed into models run on the NVIDIA Jetson edge AI platform to provide insights about crop conditions.

Pests can be identified in milliseconds with convolutional neural networks, quantified and mapped to a particular zone, enabling faster treatment. If aphids are invading, and it’s an organic farm, it might be time to release the ladybugs to gobble them up. The alternative of relying on periodic boots on the ground for inspections might otherwise lead to crop yield losses.

Ztractor machines can also handle soil preparation tasks like tilling and disking. It can work with seeding and precision weed control equipment — like smart sprayers with AI-driven cameras — to help make up for labor shortages for these tasks.

The machines can run eight to 12 hours on a charge, depending on the unit.

Jetson-Driven Tractor Autonomy

Farmers can set coordinates for the tractor’s path using satellite data or aerial images and the onboard GPS for geofencing the machines.

The tractors run the TrailNet model, processed on the NVIDIA Jetson Xavier, for real-time path planning. The neural network — trained on a custom dataset of about 500 images — was run on cloud instances of NVIDIA GPUs.

Its plug-in electric system offers a 75 percent reduction in energy costs compared with diesel tractors, according to Kvezereli. He said:

“There is a demand for zero-emission farming from both a public policy and customer perspective,”

Pilot tests of Ztractor’s system are underway at several organic garlic family farms based in Gilroy, Calif., just southeast of Silicon Valley.