Key takeaways from Salesforce's Q2: Salesforce had a strong second quarter, with revenue up 26 percent to $2.56 billion and the company on track for more than a $10 billion revenue run rate for the fiscal year. Its growth numbers aren't that surprising, of course; what's of more utility for Salesforce observers and customers is the color and context provided during the quarterly conference call. Here's a look at the highlights.
- While Salesforce has many product categories today, its core CRM is still running strong, with revenue up about 14 percent in the quarter. On the call, CEO Marc Benioff predicted that CRM will one day be a $1 trillion market opportunity. Whether that's a reflection of his taste for the bombastic or a sure thing remains to be seen.
- Salesforce is synonymous with Silicon Valley, but has been investing in growing its global footprint. More than 40 percent of new hires in the year to date have been outside the United States, said president Keith Block.
- Benioff said Salesforce is now focusing on reaching $20 billion in revenue, and in "fairly short order." And it will get there how? Here's Benioff's explanation:
I think a lot of mistakes that the other entrepreneurs have made and I can go through each one. In enterprise software specifically, it’s not to really double down at this point, again on the customer. Get absorbed in your own myopia, get absorbed in your corporate politics, get absorbed in your corporate bureaucracies and yourselves, and try to break out of yourself and recognize the most important thing, continues to be the customer.
Salesforce's AI technology Einstein "has hugely exceeded our expectations," Benioff said. He teased "exciting news" about Einstein coming at the Dreamforce event in early November, and referred to breakthroughs for AI in financial services and healthcare. It will be interesting to see how much wood Salesforce puts behind the Einstein arrow at Dreamforce: Will it have live customers telling their success stories, or only some demos and future direction?
Microsoft's Project Brainwave seeks to democratize deep learning: A new Microsoft deep learning platform codenamed Project Brainwave is heading to the company's Azure cloud in the near future. Brainwave is focused on delivering real-time AI derived from streaming data, such as from videos, sensors and search queries, according to a blog post from Microsoft Research:
The Project Brainwave system is built with three main layers: A high-performance, distributed system architecture; a hardware DNN engine synthesized onto FPGAs; and a compiler and runtime for low-friction deployment of trained models.
First, Project Brainwave leverages the massive FPGA infrastructure that Microsoft has been deploying over the past few years. By attaching high-performance FPGAs directly to our datacenter network, we can serve DNNs as hardware microservices, where a DNN can be mapped to a pool of remote FPGAs and called by a server with no software in the loop. This system architecture both reduces latency, since the CPU does not need to process incoming requests, and allows very high throughput, with the FPGA processing requests as fast as the network can stream them.
Second, Project Brainwave uses a powerful “soft” DNN processing unit (or DPU), synthesized onto commercially available FPGAs. ... Although some of these chips have high peak performance, they must choose their operators and data types at design time, which limits their flexibility. Project Brainwave takes a different approach, providing a design that scales across a range of data types, with the desired data type being a synthesis-time decision. ... As a result, we achieve performance comparable to – or greater than – many of these hard-coded DPU chips but are delivering the promised performance today.
Microsoft is working to bring Brainwave to Azure and will detail availability in "the near future," according to the blog.
POV: Brainwave is about finding practical ways to bring high-performance deep neural net capabilities to a broad market through Azure, says Constellation VP and principal analyst Doug Henschen. That's because FPGAs (field programmable gate arrays) offer a comparatively low-tech way to apply dedicated, hardware-based computing power to AI challenges without turning to more exotic hardware, such as GPU-based servers, he adds. "Rather than chasing records under controlled lab conditions, the focus is on bringing general purpose AI acceleration into commercial use as soon as possible," Henschen says.
In short, Project Brainwave is "not about conducted elite AI research in an ivory tower," he adds. "It's about bringing responsive deep neural-net capabilities to a broad community of developers that will pursue breakthrough, real-world applications of AI."
Google rolls out Chrome Enterprise: When VMWare founder and CEO Diane Green joined Google in 2015 to lead its cloud business, the prevailing view was that she would spark a wave of activity around generating more business from enterprise IT shops. Google is taking a big step in that direction with the introduction of Chrome Enterprise, a new version of the cloud-centric Chrome OS that adds on many enterprise-friendly—if not mandatory—features, such as deeper security, around-the-clock support and integration with Microsoft Active Directory.
The last feature is especially key, as it means administrators at companies can use familiar on-premises tools to manage both Windows and Chrome devices.
POV: Google made an enterprise push for Chrome devices in 2014, with the introduction of Chromebooks for Work. Chrome Enterprise builds substantially on that idea, but preserves the $50 per device/year price point, which could prove quite attractive to companies, particularly ones already invested in Google Apps. Chromebooks remain highly price-competitive as well. Google is planning to reveal more details about Chrome Enterprise during a webcast, for which registration is available at this link.