Microsoft, every mention
29 scenes (2017), the whole family · ← back to Microsoft
tap a year for its mentions
every year 2017 anyone Matt Turck 78Benedict Evans 42George Sivulka 25Amr Awadallah 18Mike Palmer 15Tomasz Tunguz 13Sandy Steier 11Mike Tuchen 11Chris Dixon 11Richard Socher 10
Verbatim, from the transcripts: the passages where Microsoft comes up
Superpowered Conversations // George Davis, Frame.ai (FirstMark's Data Driven)
- ▶ 0:42 George Davis What about, ah, MS Teams, other team chat programs?
Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
- ▶ 1:32 Auren Hoffman This is a very famous slide from Microsoft Research, and basically the slide shows that, ah, the better, ah, the, the better the data set, the bigger the data set, ah, ah, will change which algorithms win. 2 times in the scene
Cybersecurity Data at Scale // Sam Kassoumeh & Bob Sohval, SecurityScorecard (Data Driven)
- ▶ 8:34 Dr. Bob Sohval But momandpop.com is going to have a very different order of magnitude attack surface than Amazon or Microsoft.com or something of that sort.
- ▶ 10:40 Dr. Bob Sohval So, what we're looking at now is, uh, uh, granularized to, to reveal Safari, Firefox, Edge, Chrome, and so forth. 2 times in the scene
Data-Driven Real Estate Investing // Jean Sini, Cadre (FirstMark's Data Driven)
AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
- ▶ 17:11 Bradford Cross And so what it's created is a, is basically a sort of a graveyard of these companies that think that they can do what Google or Amazon or Microsoft are now trying to do with this machine learning as a service stuff. 2 times in the scene
Graph Theory and Cybersecurity Data // Liz Maida, Uplevel Security (FirstMark's Data Driven)
- ▶ 7:13 Liz Maida You know, they'll go through, they'll do all of this work, and they write up all of their findings in an eleven-page Word document that they put on SharePoint and never, no one ever reads again.
- ▶ 7:24 Liz Maida Sometimes they use access databases, but, I mean, that's about the limit of it.
AI, Big Data, and Data Governance // Stan Christiaens, Collibra (FirstMark's Data Driven)
- ▶ 6:18 Stan Christiaens And three, and this is a belief of me that could be wrong, is that actually the big tech firms, Amazon, Facebook, Google, Microsoft, and all the others, they're using AI and machine learning as their next feature war.
- ▶ 15:12 Stan Christiaens Um, the W, the digital equivalent of WD-forty and duct tape, which is Excel, spreadsheets, meetings, et cetera.
Big Data as a Service // Prat Moghe, Cazena (FirstMark's Data Driven)
- ▶ 3:02 Prat Moghe I mean, AWS was a clear leader a few years back, but now Azure's come along, and then Google's there.
- ▶ 4:38 Prat Moghe In the old days, you had SQL, and it was Teradata, Oracle, IBM, um, you know, SAP, Microsoft, a bunch of these.
- ▶ 6:54 Prat Moghe Um, what we've done is we've actually looked at how long it takes for these companies to actually move in the cloud and build around AWS, build around Azure, 2 times in the scene
- ▶ 12:54 Prat Moghe So then why do you care if this is AWS and Redshift and Azure in the East region and all that?
- ▶ 13:42 Prat Moghe Is at the bottom most layer you got cloud, which is AWS or Azure.
Fake News, Alternative Facts and the Enterprise // Satyen Sangani, Alation (FirstMark's Data Driven)
- ▶ 4:08 Satyen Sangani People use typewriters and Microsoft Word and really old movie cameras, and you could store things inside of basically video cassettes or
- ▶ 6:37 Satyen Sangani And every single person that wants to build a report can build a report, just like they might be able to do in Excel.
The Power of GPU Analytics // Todd Mostak, MapD (FirstMark's Data Driven)
- ▶ 16:44 Todd Mostak However, one of the great stories of 2016 is that all the major cloud providers, Amazon, Google, Microsoft, basically added big GPU instances to their cloud, so we're making a significant push there as well.
Location Intelligence // Jeff Glueck, Foursquare (FirstMark's Data Driven)
- ▶ 2:33 Jeff Glueck So, you know, we power a lot of the location inside Bing.
Drug Discovery as a Data Problem // Sajith Wickramasekara, Benchling (FirstMark's Data Driven)
- ▶ 3:28 Sajith Wickramasekara This is an industry that runs on paper, email, and Excel, and it's something that touches everyone.
- ▶ 5:33 Sajith Wickramasekara So, at a very high level, their original data platform consisted of Microsoft Word for documenting experiments and high-level reports.
- ▶ 5:43 Sajith Wickramasekara Excel and FileMaker Pro for tracking the actual antibodies themselves and the data associated with them. 2 times in the scene
- ▶ 8:01 Sajith Wickramasekara When we were first in contact with them, they did this using a slew of Excel spreadsheets.
- ▶ 11:22 Sajith Wickramasekara Um, since the science is so intensive, and since there are tens of thousands of candidates for any given study that need to be assessed and refined and characterized, um, it's necessary that scientists iterate on the process, and that's…
- ▶ 11:22 Sajith Wickramasekara Um, since the science is so intensive, and since there are tens of thousands of candidates for any given study that need to be assessed and refined and characterized, um, it's necessary that scientists iterate on the process, and that's…
- ▶ 12:19 Sajith Wickramasekara So just to kind of synthesize what I talked about, um, we see drug discovery moving from a paper, email, Excel world to kind of a single end-to-end application.
- ▶ 17:33 unnamed speaker Um, so the venture platform seems pretty interesting in that, you know, obviously it's a pretty efficient aggregator of data, you know, be able to put the data in a single view of it all for the first time outside of these kind of…
Project Jupyter // Jason Grout & Sylvain Corlay, Bloomberg (FirstMark's Data Driven)
- ▶ 10:05 Jason Grout Notebooks that you can download and run in a cloud service like Microsoft Azure, or click on this link and you use Jeremy Freeman's binder.
- ▶ 10:24 Jason Grout Many, many companies are actually building on top of this platform, ah, to build out, ah, computational services, including Microsoft, Google, IBM,