arauhala

5 ms·

31.
by arauhala 6y ago
Would you be our first customer, if we do it? ;-) The fact of the matter is that, while it is a tempting idea it's far from easy. The interfaces may not be that hard, but the storage itself will have its challenges and building a fast
32.
by arauhala 6y ago
Please correct me if I'm mistake, but doesn't that require a separately prepared model in both Postgres and madlib? You cannot simply request for an arbitrary prediction in a single & simple query.
33.
by arauhala 6y ago
No scripts. The change is much deeper, because Aito uses ad hoc / lazy models to provide the predictive query capabilities. If you would thinly integrate some 3rd party ML library, you would end up with separate 1) model definition and
34.
by arauhala 6y ago
I can see, why having predictive queries in solutions like Snowflake or Postgres would be extremely tempting. Still, the problem of integrating the Aito like functionality in existing databases is that it requires lot of specialized data st
35.
Return on Investment for Machine Learning(aito.ai)
3 points by arauhala 6y ago|0 comments
36.
by arauhala 6y ago
llarsson, I think you are spot on with this comment :-) Also thank you for the advice. We have indeed gotten a good response in the less-technical, but more business oriented, RPA developer community, as an addition to appealing to the trad
37.
by arauhala 6y ago
We have few customers in production. One is about smart purchase invoice automation and - IMO - the real world data set is not that different from those StatLog / UCI / Kaggle datasets. Of course our customer datasets tend to be o
38.
by arauhala 6y ago
The big thing in Aito is still, that it is 'modelless'. You don't need a prepared model to do a prediction, because the model is done ad hoc / lazily for the query. It is a much easier workflow, because you don't ne
39.
by arauhala 6y ago
The reason, why the predictive queries create value relates to the simplified workflow and the simplified architecture. Instead of defining model, training model and using model, you merely ask for an arbitrary unknown variable, based on an
40.
by arauhala 6y ago
I do understand your point. There are definately tons of hard data science problems, which are simply not suitable for the predictive query kind of approach. At the same time there are tons of ML problems e.g. in process automation or user
41.
by arauhala 6y ago
It's not just different interface, but different workflow. In traditional ML you need to a) define model to do prediction A -> B b) train the model, which may take minutes c) then do the predictions form A -> B, which takes (1,
42.
by arauhala 6y ago
Here's an early article on predictive databases: https://aito.ai/blog/introducing-a-new-database-category-the... The big difference of the predictive queries / databases compared to trained models is that pre
43.
by arauhala 6y ago
I would say, that the answer is partially yes and partially no. We have done several projects with simple machine learning problems, where e.g. semi-technical RPA developers have been able to implement ML based automation just fine. We have
44.
by arauhala 6y ago
It does sound appealing, doesn't it :-) Regarding the model: as described in the article, you can create specialized ML models in millisecond scale. This means that all computational, latency and consistency issues disappear, as you do
45.
by arauhala 6y ago
The author here. If you have any questions about the article, I'm happy to help. :-) I do believe, that the query based ML will replace the trained model based ML in the long run. I believe this not because the results would be better,
46.
by arauhala 6y ago
Hi Luc, What's your perspective on predictive databases like https://aito.ai ? I'm one of the Aito.ai founders. If you would like to hear more, I'm happy to talk one-to-one. Regards, Antti
47.
by arauhala 6y ago
Hi Peter :-) Antti from aito.ai here ( https://aito.ai ) What do you think about Aito and the predictive databases? We believe that the predictive databases can be a thing both in the database and the ML space, which is quite exci
48.
by arauhala 6y ago
Well, it's obviously not easy, but it's definitely interesting :-)
49.
by arauhala 6y ago
Hi fugenxmobileapp, I'm a Aito.ai founder. We have created a predictive DB solution, where you can get predictions / ML instantly via SQL-like queries from the database. Aito could be used to e.g. fill forms, predict users' n
50.
by arauhala 6y ago
This is extremely intesting domain. I feel that even more interesting topic than optimizing code would be in generating code to replicate a process based on input / output samples.
51.
Grim Lessons in Customer Validation(medium.com)
1 points by arauhala 6y ago|0 comments
52.
by arauhala 6y ago
Interesting looking article, but could you share the content behind the paywall?
53.
by arauhala 6y ago
This looks pretty amazing, and something I have hoped would exist. I wonder if it would make any sense to add Jupyter Notebook kind of functionality to these kinds of notes. It feels like super cool idea, but it may be too big feature to be
54.
by arauhala 7y ago
True. Aito does resemble BayesDB. BayesDB wasn't the inspiration for Aito (I found it afterwards), but it is extremely impressive piece of work. The biggest difference between BayesDB and Aito is that BayesDB is built on top of SQLite,
55.
by arauhala 7y ago
It's done for discrete data. Operations on such data can be optimized to pretty extreme level. Aito scales to around million rows and million features before slowing down too much. We believe we can make it scale to 10m or 100m rows in
56.
by arauhala 7y ago
The recommendations are content based. Basically, if you have a preference for certain item or feature, it will get better score. Compared to collaborative approach: content based scoring works better for learning routine, e.g. the weekly g
57.
by arauhala 7y ago
Aito builds a model for predictive queries in millisecond scale. It requires heavy optimizations and preparations in DB to reach the performance. The indexes are optimized for statistics, and there are extra datastructures not found in norm
58.
by arauhala 7y ago
Hi, the author here, we made predictive database to help developers test, prototype and productize predictive functionality - lighting fast. Just to be clear, the predictive database's value proposition is two fold. First: querying for
59.
by arauhala 7y ago
Aito can do statistical predicting, recommending, matching and relating, and of course normal queries and FTS search. It has been built bottom up to provide programmers ability to query unknown (like ML system) as an addition to known (like
60.
by arauhala 7y ago
Founder here. Aito had a custom database optimized for statistical operations. It essentially creates Bayesian models real time to answer the queries.

More ›