Graph based code generation where code doesn’t reside in files in the typical sense. On insertion, modification, and deletion, constraints are checked / ran to see if the change is valid and can be done or not.
I am floored at these achievements. Such amazing work.
If I may ask, when you started thinking about achieving this, what were the first attempts, ideas on how to go about it? What were some of the obstacles that had to be overcome to achieve this ?
Probably on a business / Enterprise plan, which has managed settings and also telemetry export. Give it a collector endpoint to export to and then have collector send to s3.
The thing that I keep thinking about is the accounting / charging when it downgrades automatically.
Do they adjust the price of the api request so that only the tokens that were utilized by fable get charged at that price and the remaining tokens that the cheaper / nerfed (fable) model utilizes get charged at that price?
If the answer is no, could that be construed as fraud?
What a statement. What a statement. How many financial institutions do they support? How many different vendors supply the platform for those institutions? How many of those financal institutions (FI) don’t support oauth or other APIs? A lot!
Then ask yourself: how do they talk get the data if no api? Web scraping. Then ask yourself how they build the scrapers for those? Where do those accounts come. Employees of the company who open up accounts at those FIs? What about all the other FIs? Where do you think those come from…? How do you think that process is secured? Think the process is secured enough to make you feel warm and cozy? When the scrapers are working, how do you think they get past the security measures? Do you think those financial institutions might think it’s odd that you’re logging in from multiple IPs and that one or more of those ips might be from a residential proxy network?
The result is that I attempt, at all cost to not use anything that requires plaid or their competitors since I know how that sausage is made.
> Frontier models score ~90% on Python but only 3.8% on esoteric languages, exposing how current code generation relies on training data memorization rather than genuine programming reasoning.
> Siri fell behind due to how good Apple’s privacy is.
Uhh. What the heck are you talking about? I’m calling straight bs on this unless presented rational.
Siri has access to knowledge.db or whatever it is, which is the centralized hub for pretty much all things. Siri phones home every request made via Siri.