Tesla’s least expensive car is off the market: the Model 3 Standard Range Rear-Wheel Drive is no longer available in the online configurator. first reported on the absence of that Model 3 build. It was the cheapest option from the electric vehicle brand with a price tag of $39,000. Now the takes that title with a retail price of $42,500. Tesla unveiled a to its Model 3 line in the US in January.

The company also posted for the third quarter today, with 462,890 vehicles delivered between July and September. Sales were aided by price cuts and other incentives during the quarter, enough to reach a 6.4 percent increase from the previous year’s deliveries. However, the figure fell short of analysts’ predictions for more than 469,000 deliveries during the period. This quarterly result could also hamper CEO Elon Musk’s projections for the company to surpass the 1.8 million vehicles it handed over in all of 2023.

Tesla has also been struggling with recalls this year. Most of those issues were fixed with over-the-air updates, but the scope and number of the issues may also be leaving customers with doubts. Recalls impacted vehicles in January, in February, in May, in June, in July, and more than in August.

As the generative AI continues to progress, having a simple chatbot may no longer be enough for many enterprises.

Cloud hyperscalers are racing to build up their databases and tools to help enterprises deploy operational data quickly and efficiently, letting them build applications that are both intelligent and contextually aware.

Case in point: Google Cloud’s recent barrage of updates for multiple database offerings, starting with AlloyDB.

According to a blog post from the company, the fully managed PostgreSQL-compatible database now supports ScaNN (scalable nearest neighbor) vector index in general availability. The technology powers its Search and YouTube services and paves the way for faster index creation and vector queries while consuming far less memory.

In addition, the company also announced a partnership with Aiven for the managed deployment of AlloyDB as well as updates for Memorystore for Valkey and Firebase.

Understanding the value of ScaNN for AlloyDB

Vector databases are critical to power advanced AI workloads, right from RAG chatbots to recommender systems.

At the heart of these systems sit key capabilities like storing and managing vector embeddings (numerical representation of data) and conducting similarity searches needed for the targeted applications. 

As most developers in the world prefer PostgreSQL as the go-to operational database, its extension for vector search, pgvector, has become highly popular. Google Cloud already supports it on AlloyDB for PostgreSQL, with a state-of-the-art graph-based algorithm called Hierarchical Navigable Small World (HNSW) handling vector jobs.

However, on occasions where the vector workload is too large, the performance of the algorithm may decline, leading to application latencies and high memory usage.

To address this, Google Cloud is making ScaNN vector index in AlloyDB generally available. This new index uses the same technology that powers Google Search and YouTube to deliver up to four times faster vector queries and up to eight-fold faster index build times, with a 3-4x smaller memory footprint than the HNSW index in standard PostgreSQL. 

“The ScaNN index is the first PostgreSQL-compatible index that can scale to support more than one billion vectors while maintaining state-of-the-art query performance — enabling high-performance workloads for every enterprise,” Andi Gutmans, the GM and VP of engineering for Databases at Google Cloud, wrote in a blog post.

Gutmans also announced a partnership with Aiven to make AlloyDB Omni, the downloadable edition of AlloyDB, available as a managed service that runs anywhere, including on-premises or on the cloud.

“You can now run transactional, analytical, and vector workloads across clouds on a single platform, and easily get started building gen AI applications, also on any cloud. This is the first partnership that adds an administration and management layer for AlloyDB Omni,” he added.

What’s new in Memorystore for Valkey and Firebase?

In addition to AlloyDB, Google Cloud announced enhancements for Memorystore for Valkey, the fully managed cluster for the Valkey in-memory database, and the Firebase application development platform. 

For the Valkey offering, the company said it is adding vector search capabilities. Gutmans noted that a single Memorystore for Valkey instance can now perform similarity search at single-digit millisecond latency on over a billion vectors, with more than 99% recall. 

He also added that the next version of Memorystore for Valkey, 8.0, is now in public preview with 2x faster querying speed as compared to Memorystore for Redist Cluster, a new replication scheme, networking enhancements and detailed visibility into performance and resource usage. 

As for Firebase, Google Cloud is adding Data Connect, a new backend-as-a-service that will be integrated with a fully managed PostgreSQL database powered by Cloud SQL. It will go into public preview later this year.

With these developments, Google Cloud hopes developers will have a broader selection of infrastructure and database capabilities — along with powerful language models – to build intelligent applications for their organizations. It remains to be seen how these new advancements are deployed to real use cases, but the general trend indicates the volume of gen AI applications is expected to soar significantly.

Omdia estimates that the market for generative AI applications will grow from $6.2 billion in 2023 to $58.5 billion in 2028, marking a CAGR of 56%.

Transportation and freight network giant J.B. Hunt is searching for software and digital products that will fuel its business and help it adapt to the modern world — and even dominate the industry. And it’s tapping startup incubator UP.Labs to help build them. 

On Wednesday at the UP.Summit event in Bentonville, Arkansas, the two companies announced a logistics and freight venture lab that will launch up to six startups over the next three years. The first of these startups is slated to launch in 2025 and will focus on some of the biggest problems in logistics and freight. 

UP.Labs isn’t structured like the many startup incubators that exist today. And while the company does operate in parallel with venture firm UP.Partners and uses some underlying concepts found in the venture capital world, it is not a traditional VC firm.

Instead, UP.Labs is a venture lab with a financial investment vehicle. The company forms agreements with major corporations to solve a problem for that company and for the wider sector. These aren’t meant to be proof-of-concept ideas. Instead, these startups are designed to operate independently and commercially. 

Importantly, UP.Labs doesn’t allow the corporate partner to invest more than their pro rata in any of the financing rounds because it can make it difficult to attract talent and future investors. After three years, the corporate partner has the option to acquire the remaining shares of the startup. They will use a third-party valuation firm to determine the fair market value.

The opportunity to develop logistics startups focused on software and data is vast, UP.Labs founder and CEO John Kuolt told TechCrunch in a recent interview. 

This is the third venture lab launched by UP.Labs and a major corporation since it launched in 2022. Its first partner was Porsche, which represents the automotive sector. Under that partnership, several startups have launched, including Pull Systems, which developed performance management software for EV suppliers, manufacturers, and operators. The lab also created Sensigo, a startup that is working on software to help service technicians diagnose problems in modern, software-defined vehicles in a matter of minutes, instead of days.

Last year, UP.Labs formed an aviation-focused lab with Alaska Airlines. Odysee, the first startup born out of that lab, made its public debut at the UP.Summit. 

Overall, UP.Labs has launched 10 companies — including four with Porsche and two with Alaska Airlines — in the past 2.5 years, according to Kuolt. 

“Startups are not new for us,” J.B. Hunt president and CEO Shelley Simpson said at the UP.Summit, noting the business has transformed from a legacy truck carrier to being one of the largest transportation logistics companies. That transformation required innovation within the company and tapping outside partners. For instance, Walmart, Tyson Foods, and J.B. Hunt partnered in 2019 with accelerator network Plug and Play to set up a logistics-focused program in Northwest Arkansas.

What’s different this time, she said on the sidelines of the UP.Summit event, is how this venture lab operates.

“We don’t think we’re the ones who can solve everything,” Simpson said. “We recognize the market is very large and we certainly think we have good, smart people, but we also know there’s really smart people out there, and anytime we can find a good partner, that’s going to be important for us.”