In a year like no other in recent memory, the data ecosystem is showing not just remarkable resilience but exciting vibrancy. When COVID hit the world a few months ago, an extended period of gloom seemed all but inevitable. Cloud and data technologies (data infrastructure, machine learning / artificial intelligence, data driven applications) are at the heart of digital transformation. As a result, many companies in the data ecosystem have not just survived, but in fact thrived, in an otherwise overall challenging political and economic context. Perhaps most emblematic of this is the blockbuster IPO of Snowflake, a data warehouse provider, which took place a couple of weeks ago and catapulted Snowflake to a $69B market cap company, at the time of writing – the biggest software IPO ever (see our S-1 teardown).
Artificial intelligence, or AI, refers to the ability of tools or technology to perform tasks that would normally require human intelligence to complete. Machine learning is a subset of AI in the computer science space – where the platform or model learns from an existing data set so that it can understand the underlying trends and patterns. This knowledge is then used by the machine learning models to make predictions or determine outcomes from the new data it encounters. In other words, the computer model uses statistical techniques to learn how to get better at a task, whether that be categorizing data or predicting if a client is a good fit for a certain product. For the model to learn to do this without specific programming, it must analyze existing data that is already pre-labeled.
Google held its "Launch Night In" event on Wednesday, the pandemic version of its annual hardware reveal. The company announced its latest phones, speaker, and streaming device. The Google Pixel 5 in Sorta Sage... for when you can't decide if sage is really your brand. SEE ALSO: Google's new Chromecast puts all your streaming apps into one slick interface Google's new phones have arrived! Meanwhile, the Pixel 5 is made of 100 percent recycled aluminum, and is just a tiny bit bigger with a 6.1-inch OLED screen.
Inside an ordinary-looking home, a robot suspended from the ceiling slowly expands arms holding a sponge, before carefully wiping a kitchen surface clean. Nearby, another robot gently cleans a flat-screen television, causing it to wobble slightly. The cleaning robots live inside a mock home located at the Toyota Research Institute in Los Altos, California. The institute's researchers are testing a range of robot technologies designed to help finally realize the dream of a home robot. After looking at homes in Japan, which were often small and cluttered, the researchers realized they needed a creative solution.
MacGyver-like savviness is needed for AI, including self-driving cars. Who or what is a MacGyver, you might wonder? Well, most people have heard of MacGyver, the TV series and main character that manages to always find a clever means to extricate himself from some puzzling predicament, using his wits to devise a solution out of rather everyday items. Fans know that he carries a Swiss Army knife, rather than a gun, since he believes that using his creativity and inventiveness will always allow him to deal with any untoward circumstance (the knife is handy when you need to defuse a bomb, or when you need to take apart a toaster and reuse its electronics for a completely different purpose and ultimately save your life accordingly). Turns out that you don't necessarily need to have ever seen the show or watched any YouTube clips and yet still nonetheless might know what it signifies to be a "MacGyver" in dealing with a thorny task (it has become part of our lexicon of speaking).
Determining the valuation of an early-stage Startup is in most cases very challenging due limited historical data, little to no existing revenues, market uncertainty and many more. Traditional valuation techniques, such as Discounted Cash Flow (DCF) or Multiples (CCA), therefore often lead to inappropriate results. On the other hand, alternative valuation methods remain subject to an individual's subjective assessment and a black box for others. Therefore, the underlying study leverages machine learning algorithms to predict a fair, data-driven and comprehensible startup valuations. Three different data sources are merged and applied to three regression models.
As many of you will know, artificial intelligence is a passion of mine. I believe in its potential to boost productivity, solve problems, and make the world a better place. For me, it's more than just talk; I am building an entire business around AI and I stand with the users and creators of AI who see its potential and the exciting places it can take us. But not everyone is like us. Despite growing body evidence to the contrary, many people still see AI as a dark force; a development to be feared instead of celebrated.
The latest enhancements include the addition of global ocean visibility and expansion of B2B connectivity for truckload and less-than-truckload (LTL) freight contracting. These brand-new native integrations are the next step towards delivering on a joint multi-modal strategy to provide organizations with a single view across their end-to-end supply chains. Driven by a shared vision of a fully connected and transparent logistics network, project44 and SAP joined forces in 2019 to enable B2B connectivity and collaboration, empowering global companies to create more resilient supply chains and make smarter decisions across their logistics workflows with real-time access to high-fidelity data. "With the uncertainty global companies are facing today, supply chains are at their breaking point, and logistics is what interconnects the entire process. Shippers need visibility data to steer their entire supply chain," said Paige Cox, SVP and Head SAP Business Network.
Android's machine learning renaissance is coming to the Photos app, company executives announced during Wednesday's gloriously brief Pixel 5 live stream event. To start, Google plans to augment its already useful image auto-enhance feature with machine learning algorithms that can further improve those enhancements based on the specific image you're working on. Users will be able to apply brightness, contrast and portrait effects with a single tap to start with Enhance and Color Pop filters being rolled out in a few months. And for photographers that prefer to edit their shots manually, Google reorganized the editor layout into a scrollable bar across the bottom of the screen. The company is also offering an AI-based lighting feature, dubbed Portrait Light, that can apply varying levels and differing positions of light and shadow to a photo you've already taken.