tixocloud

14 ms·

91.
by tixocloud 6y ago
Thanks for sharing. It’s interesting to see the space gaining steam. What sort of things are people looking at?
92.
by tixocloud 6y ago
Exactly this. The unreasonable expectations of what AI can do - whilst it can speed things up significantly, majority of cases, you can never fully automate everything with AI.
93.
by tixocloud 6y ago
That's an interesting scenario. Does the well known large enterprise have a venture arm? We see a plethora of corporate venture firms who are intrigued by what we're working on. For us to work with them to get access to a larger c
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by tixocloud 6y ago
Curious - what made you go with Salesforce?
95.
by tixocloud 6y ago
TLDR: Reframe the data duplication problem into a business problem. It's an incredibly tough problem and I haven't seen it solved with technology alone (mind you, I've been working at banks for the last few years and have usu
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Ask HN: Workflow and Document Management Recomendations?
2 points by tixocloud 6y ago|0 comments
97.
by tixocloud 6y ago
Any reason why? Seems to be a strong digital payments ecosystem in the U.K. and Europe that would've made it work well.
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by tixocloud 6y ago
It could be an app - we've had startups approach us to sell location data collected from apps so I wouldn't rule anything out at this point.
99.
by tixocloud 6y ago
How easy would it be to estimate costs based on something like data points/performance traces? On the one hand, it makes total economic sense to align pricing against utility but I’ve also heard for larger enterprises, something that l
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by tixocloud 6y ago
Check out https://www.nocsdegree.com/ made by a friend of mine. You'll see that there are plenty of cases where you don't need formal education as long as you have the drive. For applying to jobs, consider being c
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by tixocloud 6y ago
Yes agreed. That would be very helpful indeed. Even more so, which partners invested in which companies would also be good.
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by tixocloud 6y ago
Most shitty deal flow gets ignored and it doesn’t serve founders well. The best approach is to spend time to research the firm and the partner you’re looking to seek investment from. You’ll get results when what you’re building matches what
103.
by tixocloud 6y ago
>> they indirectly holding them through some sort of pension -> managed fund -> ??? style chain where they are exposed to the madness without realising it. This is the main reason why big companies are never allowed to fail. Why
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by tixocloud 6y ago
Definitely. Even as an engineer working on CV 10 years ago, the hard part wasn’t object detection but rather network bandwidth to stream incredible amounts of data and processing it in real-time. Spoke to an experienced engineer who used to
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by tixocloud 6y ago
Another point is that while we technologists love to marvel at data science and machine learning, it still begs the question of what value does it bring to the business. Does the added responsibility of creating all the infrastructure and p
106.
by tixocloud 6y ago
Completely spot-on. Too many "all-in-one" platforms are just too rigid and with AI infrastructure tooling still in the early stages, the companies that adopt modular products will be able to capitalize on new advances.
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by tixocloud 6y ago
Huge insight and definitely on point. Where I've worked, data science teams are focused on business impact. More responsibility requires larger budgets and at times, creates a burden. Plus I have a sense not a lot of senior executives
108.
by tixocloud 6y ago
You've brought up a lot of very interesting points that we're actually looking to solve regarding data distribution changes, data version control and reproducibility, privacy guards and bias detections with our startup Orchestra (
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by tixocloud 6y ago
This. In my experiences across larger enterprises, data science teams rarely hold the key to production environments and therefore, relies heavily on IT to productionizing ML. And I completely agree that data scientists need to be focused o
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by tixocloud 6y ago
It’s similar to our viewpoint as well. Currently, it’s easy to see gains because we’re mainly going from highly manual processes to 1st generation AI applications. Future generation AI applications will mostly be optimization and squeezing
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by tixocloud 6y ago
This is a valid approach and is commonly used even with large enterprises. It's also the route we're taking with our startup as it lowers the initial friction and allows you to build out credibility. This is also the approach I us
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by tixocloud 7y ago
1. By unbiased, do you mean opinionated? The MLOps industry is still in the very early stages and there’s no single standard. Every dev and company has come up with an implementation but there are so many tiny little use cases that sometime
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by tixocloud 7y ago
Have you previously tried joining a social group unrelated to the subject that creates the anxiety? Also, have you tried meditation, chanting or studying topics such as philosophy? Happy to connect and walkthrough my own personal experience
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Ask HN: Anyone use Git for ML code version control?
1 points by tixocloud 7y ago|1 comments
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by tixocloud 7y ago
Would love to have a promo code and happy to promote your service in exchange as well. Thanks. Looks very useful!
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by tixocloud 7y ago
Sorry - perhaps there is little difference if any between neobanks vs regular challenger banks. Neobanks would be digital-only type banks while regular challenger banks are heavily skewed digitally but have the backing of an existing incumb
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by tixocloud 7y ago
As a banking strategist, neobanks are what we're mostly concerned with vs regular challenger banks. The primary reason is the disintermediation from the customer through a particular service. Customer touchpoints for purchases and serv
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by tixocloud 7y ago
As William Gibson once said “The future is already here. It’s just not evenly distributed”. First mover advantages are less becoming of an advantage because of how fast information travels. The other obstacle with being first movers is the
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by tixocloud 7y ago
Would really be interested in the project. We’re building a tool to monitor model performance and data patterns and could see use of this.
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by tixocloud 7y ago
I’m working on building monitoring and analytics for machine learning (visualizing patterns of data around the data pipeline and model itself). You’d be able to track long term and short term data distribution changes so you have an idea of

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