Now rebranded as Mosaic AI, the platform has become integral to Databricks’ AI solutions.
Today, at the company’s Data + AI Summit, it is launching a number of new features for the service.
Databricks is launching five new Mosaic AI tools at its conference: Mosaic AI Agent Framework, Mosaic AI Agent Evaluation, Mosaic AI Tools Catalog, Mosaic AI Model Training, and Mosaic AI Gateway.
And we’ve also found in our internal AI applications, like the assistant applications for our platform, that this is the way to build them,” he said.
But when you really pushed people, they were using Open AI.
That means there’s a market for a layer between companies and Large Language Models (LLMs) — something companies can use to pick LLMs easily without needing to commit for all time to one platform.
That’s the market Langdock is targeting with its chat interface that sits between LLMs and a company.
“Companies don’t want to have a vendor lock-in on just one of those LLM providers,” Lennard Schmidt, co-founder and CEO of Langdock, told TechCrunch.
In addition to the chat interface, the company also offers security, cloud and on-premises solutions.
In contrast, Langdock’s chat interface works for a broader range of use cases and can be used by any kind of staff.
Web browser company Opera announced today it will now allow users to download and use Large Language Models (LLMs) locally on their computer.
This feature is first rolling out to Opera One users who get developer stream updates and will allow users to select from over 150 models from more than 50 families.
The feature will be available to users as part of Opera’s AI Feature Drops Program to let users have early access to some of the AI features.
Notably, Opera is not doing any work to save storage while downloading a model.
“Opera has now for the first time ever provided access to a large selection of 3rd party local LLMs directly in the browser.
“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.
Even when some or all of those are addressed, there remains the question of what happens when a system makes an inevitable mistake.
We can’t, however, expect consumers to learn to program or hire someone who can help any time an issue arrives.
Thankfully, this is a great use case for LLMs (large language models) in the robotics space, as exemplified by new research from MIT.
“LLMs have a way to tell you how to do each step of a task, in natural language.
It’s a simple, repeatable task for humans, but for robots, it’s a combination of various small tasks.
At the moment, large organizations often employ “business intelligence” (BI) tools to figure out what the heck is going on inside their operations.
Essentially, BI tools connect to a business database and use SQL to create visualizations and build out BI dashboards.
There are huge companies involved in this space: Tableau (owned by Salesforce), Power BI (owned by Microsoft), Looker (owned by Google), and QuickSight (owned by Amazon) to name just a handful.
And how is this marketing campaign performing.” He said other players in the market target data users, whereas Fluent targets the business market, not data.
For example, Metabase is an open-source analytics and business intelligence application that allows users to create dashboards more easily.
Chinese tech companies are gathering all sorts of resources and talent to narrow their gap with OpenAI, and experiences for researchers on both sides of the Pacific Ocean can be surprisingly similar.
The parallel glimpse into their typical day reveals striking similarities, with wake-up times at 9 a.m. and bedtime around 1 a.m.
Both start the day with meetings, followed by a period of coding, model training and brainstorming with colleagues.
Besides building its own LLM in-house, Alibaba has been aggressively investing in startups such as Moonshot AI, Zhipu AI, Baichuan and 01.AI.
Facing competition, Alibaba has been trying to carve out a niche, and its multilingual move could become a selling point.
Google releases new open LLMs, Rivian lays off staff and Signal rolls out usernamesWelcome, folks, to Week in Review (WiR), TechCrunch’s regular newsletter covering noteworthy happenings in the tech industry.
This week, Google launched two new open large language models, Gemma 2B and Gemma 7B, in its continued bid for generative AI dominance.
The company, which describes the LLMs as “inspired by Gemini,” its flagship family of GenAI models, made each available for commercial and research usage.
Change Healthcare hit: Change Healthcare, one of the largest healthcare tech companies in the U.S., confirmed that a cyberattack on its systems occurred recently.
YouTube triumphant: YouTube dominates TV streaming in the U.S., per Nielsen’s latest report.
Barely a week after launching the latest iteration of its Gemini models, Google today announced the launch of Gemma, a new family of lightweight open-weight models.
To get started with Gemma, developers can get access to ready-to-use Colab and Kaggle notebooks, as well as integrations with Hugging Face, MaxText and Nvidia’s NeMo.
While Google highlights that these are open models, it’s worth noting that they are not open-source.
Indeed, in a press briefing ahead of today’s announcement, Google’s Janine Banks stressed the company’s commitment to open source but also noted that Google is very intentional about how it refers to the Gemma models.
“[Open models] has become pretty pervasive now in the industry,” Banks said.
As conversational AI begins to take over the world, chatbots are being given a new lease of life.
Parcel delivery giant DPD recently had to disable part of its online support chatbot after it swore at a customer.
The demand for conversational AI is skyrocketing, and is set to explode to a mind-boggling $38 billion globally by 2029.
However, regulated sectors are still grappling with Natural Language Understanding (NLU) and Large Language Models (LLMs).
While an LLM might be able to sound like a human and understand context, regulated industries need high guard rails on an AI-driven approach.
