And they’re calling their company… The Mobile-First Company.
Too many companies that offer B2B tools treat mobile apps as companion apps and second-class citizens.
Small companies don’t need a complicated enterprise software solution.
While Siel Brunet is more experienced with the needs of large companies, he has also seen how B2B apps don’t work well with small businesses.
Many small companies simply rely on consumer apps to fill their needs.
Vibrant Planet looks to be one of those solutions.
The startup digitizes land mapping and uses AI to help its users — fire departments and government bureaus — better manage land and also better prepare for potential climate incidents like wildfires.
“[It’s] very collaborative with spatially overlapped plans.”Moving the mapping online also allows organizations to work together on land management solutions that work for everyone.
“Vibrant Planet is a science and technology platform that is creating what we call a common operating picture for wildfire resilience and nature resilience,” Wolff said.
And we’re using it in the natural resource management and wildfire resilience building space, because we have to, it’s very urgent.”
Today, large swaths of the globe haven’t adopted air-source heat pumps because they don’t work as well when the mercury drops.
What’s more, the refrigerants most heat pumps use are either potent greenhouse gases or can break down into forever chemicals, researchers have found.
Heat pumps are used not just to heat and cool homes and vehicles, but also to generate heat for industrial processes, dehumidify buildings, keep food cold in grocery stores, and more.
The Biden administration announced in February that it was devoting $63 million from the Defense Production Act to boost heat pump manufacturing specifically.
Now it just has to get its super-fast compressors into production in time to catch the wave of heat pump adoption.
What do you call an AI company that is suffering from very public gyrations regarding its business health, place in the market, and leadership structure?
Well, you might call it Stability AI.
Stability AI’s latest leadership shakeup is no joke, with its CEO Emad Mostaque departing to work on AI products that are less centralized — which is to say, owned and built by a single company, like, say, Stability AI.
The startup’s fundraising journey is well-known to tech folks, while its best-known product — Stable Diffusion — is known even more broadly.
We dig into all that and more in today’s TechCrunch Minute:
Sila, Group14, Envoix, and Amprius are all trying to commercialize their silicon anode technology, hoping to cash in on consumers’ desire for ever more EV range.
Ionobell, a seed stage startup, is hoping to be at the top of that list, claiming its silicon material will be cheaper than the established competition.
Both established companies impregnate porous graphite structures with silicon; Sila also adds a coating to the particles.
Ionobell’s silicon supply comes from a waste material, Neivert said, which helps keep costs down.
Like other battery materials companies, Ionobell faces a challenging road ahead.
“Thoras essentially integrates alongside a cloud-based service and it consistently monitors the usage of that service,” company CEO Nilo Rahmani told TechCrunch.
They launched the company right after the first of the year and closed their pre-seed funding just a few weeks ago.
In terms of AI, the company currently uses more task-based machine learning than generative AI and large language models (LLMs).
“A lot of the problems that we’re facing are systemic issues, and there are a lot of numbers involved.
They see LLMs being more useful in troubleshooting after the fact at some point as they fill out the product.
But that’s how things are at Microsoft now: everything needs to have a Copilot angle — even its most straightforward hardware events.
“Windows 11 and Windows 365 promise a new era of AI productivity,” Melissa Grant, Microsoft’s senior director for Windows Enterprise said.
Microsoft is also betting on cloud PCs delivered through Windows 365 as a surface for the Copilot.
Microsoft says that Windows App usage has now reached over 3 million active hours since it entered preview at the Microsoft Ignite 2023 in November.
And those Windows 365 cloud PCs?
Part of the shift to AI comes internally by building, some come via acquisitions and some come from partnering widely, says VP of corporate business development Philip Kirk.
Lara Greden, an analyst at IDC who covers ServiceNow, says going beyond building is a big part of every company’s strategy when it comes to AI.
“Like other major waves of technology innovation, breakthrough capabilities in generative AI are coming through entities that have laser focused on the tech itself, in other words: startups.
“ServiceNow’s focus has been on integrating generative AI to improve entire workflows, not just single processes or tasks.
They also play an important role in guiding customers with best practices around data governance and control.”The Washington release is available starting on Wednesday for all ServiceNow customers.
TigerEye CEO Tracy Young and her husband and CTO Ralph Gootee helped build their previous startup, PlanGrid, into a $100 million ARR business before selling it to Autodesk for $850 million in 2018.
Yet in spite of that success, they always felt they left business on the table because of an inability to forecast business changes accurately.
“TigerEye is a business simulation engine that helps companies predict their future,” Young told TechCrunch.
The couple was advising other startups at Y Combinator in 2021 when they decided it was time to build TigerEye.
The following year, they brought a bunch of the core members of the PlanGrid team back together and started working on the problem.
At its GTC conference, Nvidia today announced Nvidia NIM, a new software platform designed to streamline the deployment of custom and pre-trained AI models into production environments.
NIM takes the software work Nvidia has done around inferencing and optimizing models and makes it easily accessible by combining a given model with an optimized inferencing engine and then packing this into a container, making that accessible as a microservice.
Nvidia is already working with Amazon, Google and Microsoft to make these NIM microservices available on SageMaker, Kubernetes Engine and Azure AI, respectively.
Some of the Nvidia microservices available through NIM will include Riva for customizing speech and translation models, cuOpt for routing optimizations and the Earth-2 model for weather and climate simulations.
“Created with our partner ecosystem, these containerized AI microservices are the building blocks for enterprises in every industry to become AI companies.”
