Declarative DSL is a really interesting approach, especially since you’re exposing it directly to the users. There are some applications where throwing the dice in production by having LLM as part of the runtime is not an option.
Can someone please explain why does this work? Did they agree what everyone would be playing? I am not a musician, but it seems like tempos and time signatures do not match. Or is the whole point that they didn't agree to anything upfront and it still somehow works? Are they all actually playing in B-flat?
We launched LHC@home 2.0 at CERN around the time LHC itself was getting launched https://lhcathome.cern.ch/lhcathome/. The project is still going and there are thousands of people from all over contributing.
Not yet because honestly we were able to get to where we needed in terms of accuracy without it. Creating a feedback loop and turning into an agent-style interaction can be helpful for more complex automations, but honestly, you can get a lot of mileage out of what we have. Having said that, agents look really fascinating and some demos I saw are mind blowing, so we will definitely look into it very closely.
Come work at Bardeen! email me artem@ if you're interested
On a more serious note, we have built a DSL and an engine for executing automations inside the browser. Where possible we connect natively to the apps we're integrating with (like Calendar or Notion), where it's not possible (like LinkedIn) we use browser capabilities to interact or get data. We use a GPT model to transform the description of automation to our DSL, we then verify it, typecheck it, fill in the gaps where possible and present it to the user. If the user likes it they can save it and start using it. Happy to share more details if it's interesting.
It's similar to javascript, but not exactly identical. Here is an example that sends a summary of calendar event two minutes before it starts (uses gmail, openai and slack):
```
function (recipient) {\n
when: __0 = GoogleCalendar.when_next_event_is_in(time: B.Duration(120000));\n
__1 = GoogleCalendar.get_next_event();\n
__2 = OpenAI.get_summary_of(text: __1.description);\n
__3 = BardeenCommons.get_string_concatenating_strings(strings: ["Your next event is:", __1.summary, "at", __1.startTime, "Here is a summary of the event:", __2]);\n Slack.send_message(message: __3, recipient: recipient);\n}'
```
Initial accuracy was about 10%, which was pretty meh TBH. With a lot of tweaking and tuning we were able to get it to 70%. This means that it takes about 2-3 attempts to get it to generate what's expected.
The great thing is that we only use AI to generate the DSL description of the automation and let the user tweak and tune it. Once it's there we just execute it with our engine.
It's Artem, Co-Founder of Bardeen here. We launched Magic Box today and I wanted to share it with you.
It takes automation descriptions in English and turns them into in-browser playbooks that can either be launched via shortcut or triggered by an external event (such as an email arriving).
I think it's pretty cool and it's ready for anyone to try it out (no waitlist!). We currently have about 30 productivity apps integrated. Please give it a shot and let us know what you think.
What was the most interesting thing that you learned while implementing the WAL? Have you thought about how WAL is going to work in the multi-master setup?
Erlang is really good for programming highly-scalable and fault tolerant distributed systems. It was designed by Ericsson (large Telco manufacturer from Sweden) for running on Telco equipment that has extremely stringent uptime and availability requirements.
What does this mean for clouds? Are they also supposed to restrict access to GPUs for customers from Russia and China? How are clouds supposed to figure out whether a given account is “from Russia or China”?
Hey everyone, we're going through YC Startup school and put together a Notion template that helps to stay on track. Please give it a shot and let us know.
The not so happy thing about this is that at this point the entire web is somewhat flawed. Too many sites have produced too much junk content just to game Google. A fundamentally new approach is needed to identify and surface “organic” (whatever that may mean) results. So I suspect (albeit with no data to show for it) that even if we just switched all ads off we still wouldn't be happy with the results that we see.
Google’s revenue model has been at odds for far too long with identifying and weeding out SEO spam. I don't mean 'spam' here in a derogatory way, but rather everyone who has a legitimate and interesting product and has had their back against the wall and was forced to play the SEO game and become a 'search spammer'
As a result 'spammers' (again, pretty much every site these days) 'won' because it was and still is the only way to survive.