It’s something Apple is striving to answer with its own take on the category, Apple Intelligence, which was officially unveiled this week at WWDC 2024.
Apple Intelligence is a more bespoke approach to generative AI, built specifically with the company’s different operating systems at their foundation.
It’s a very Apple approach in the sense that it prioritizes a frictionless user experience above all.
The operating systems also feature a feedback mechanism into which users can report issues with the generative AI system.
This should function the same with all external models Apple partners with, including Google Gemini.
AirChat, the buzzy new social app, could be great – or, it could succumb to the same fate as ClubhouseOver the weekend, another social media platform exploded into the fray: AirChat.
Built by AngelList founder Naval Ravikant and former Tinder exec Brian Norgard, Airchat takes a refreshingly intimate approach to social media.
What I do consider a red flag is AirChat’s naive approach to content moderation.
Clubhouse’s approach to content moderation was even more permissive, since there was no way to block people for months after launch – AirChat already has block and mute features, thankfully.
With this minimalist approach to content moderation, it’s not hard to see how AirChat could get into hot water.
As Walmart works to remain competitive, it’s taking a more piecemeal approach to automation, through partnerships with a range of different robotics firms.
On Thursday, the mega-retailer announced a partnership with Fox Robotics, which brings 19 of the Austin-based startup’s robotic forklifts to its distribution centers.
Today’s news follows a 16-month pilot, which found Walmart trialing the technology in Distribution Center 6020.
DC 6020 is the place where Walmart began trials with Symbotic’s package sortation and retrieval technologies.
Following that successful trial, Walmart announced plans to roll out the technology to all 42 of its Regional Distribution Centers — that was nearly double the original target of 25.
Venture capitalists’ appetite for fusion startups has been up and down in the last few years.
The road to true fusion power remains long, but the kicker is that it’s no longer theoretical.
He added the timeline was to be able to get to fusion energy by the mid-2030s.
If we manage to get to that then the middle of the 2030s is possible.”The startup’s investors are equally convinced.
And there are at least 43 other companies developing nuclear fusion technologies.
“[W]e await feedback from the Irish Data Protection Commission [DPC], our lead data protection regulator in the EU,” he added.
While Meta’s compliance with the GDPR is led by the Irish DPC, under the regulation’s one-stop-shop.
This structure does not mean the Irish authority gets final say on Meta’s compliance with EU privacy rules, though.
In the case of Meta, this has frequently led to objections from other data protection authorities which have landed stiffer enforcements than the DPC originally proposed.
So who gets the final say on the GDPR compliance of Meta’s consent mechanism is complex too.
Almost a decade ago, Desktop Metal was one of the early darlings in accessible 3D printing in metal.
Last year, Stratasys tried to merge with Desktop Metal in a $1.8 billion deal, but the deal fell through, and these days, Desktop Metal is worth less than $210 million.
In June 2020, he split off and started his own thing — Fluent Metal — which is taking a different technology path than Desktop Metal’s technology.
It accomplishes this through liquid metal printing technology, which it hopes will set a new standard in additive manufacturing.
“In the near term, Fluent Metal will spark the imagination of designers, engineers, and technologists to consider how rapid, on-demand production of custom metal parts could transform their capabilities.
An engineer by training, Meyerowitz leans heavily on that concept at Clairity Technology, the direct air capture startup he founded in 2022.
The company is currently working on the next size up, which should be able to capture one metric ton per year.
Clairity is one of the latest entrants into the direct air capture (DAC) market, where companies compete to remove carbon dioxide from the atmosphere at the lowest cost.
He and his team, now eight strong, have designed a box that’s “good enough” to capture carbon dioxide over 80% purity, he said.
By using carbon dioxide as an ingredient, “it improves the quality of the concrete.
Cover slide Funding timeline slide Problem slide Solution slide Product slide Strategy slide Product portfolio slide Market size slide How it works slide U.S. market opportunity slide Global market opportunity slide Vision slide Team slide (?)
But it’s interesting to see Doola take a different tack to arrive at a potential market size of $4.5 billion per year.
As I mentioned earlier, there’s a vast amount of information missing from this pitch deck.
So much, in fact, that it is essentially useless as a traditional pitch deck.
In the rest of this teardown, we’ll look at three things Doola could have improved or done differently, along with its full pitch deck!
When Anomalo’s co-founders left Instacart in 2018, they thought they could put machine learning to work to solve data quality problems inherent in large data sets.
Five years later, the company’s idea is even more relevant as data quality takes center stage with large language models.
Today, the startup announced a $33 million Series B, equaling their 2021 Series A and bringing the total raised to $72 million, according to the company.
As companies store increasingly large amounts of data in cloud storage and data warehouses like Databricks and Snowflake, this need has only become more pronounced, he says.
SignalFire led the $33 million Series B investment with participation from strategic investor Databricks Ventures.
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.
