[HN Gopher] Meet your AI Executive Assistant
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Meet your AI Executive Assistant
Author : jamest
Score : 25 points
Date : 2023-09-20 16:11 UTC (6 hours ago)
(HTM) web link (www.shortwave.com)
(TXT) w3m dump (www.shortwave.com)
| anant wrote:
| I was in the early beta and judging from how it's worked in my
| tests, there's definitely more going on under the hood then the
| most straightforward approach of "embed all your emails, find
| nearest neighbors, then ask the LLM to answer".
|
| Kudos on innovating around applying LLMs to real-world problems
| and going beyond the bog-standard approach. It'd be interesting
| to see a more detailed blog on the technical approach you took!
| figassis wrote:
| I was ready to give you my money, but you're Gmail only, sorry, I
| migrated out so will wait for IMAP support.
| mayop100 wrote:
| Non-Gmail support is on our list!
| hn_user2 wrote:
| I was also was ready to add a credit card but have also moved
| off gmail.
|
| The concept sounds great though, I have to imagine there is
| another product out there, or will be soon, that does not
| require gmail.
| distract8901 wrote:
| It really hurts my head to even think about how that works.
| Does google offer some proprietary email api that isn't IMAP?
| Why would such a thing exist? Why would you make an email app
| without IMAP?
| figassis wrote:
| They're outsourcing identity verification to gmail to replace
| the "email verification flow". This way they don't have to
| configure any email infra like sendgrid, ses, etc, deal with
| bounces and so on. It's also possible gmail has better API
| support to process a lot of email, but I have seen this in
| products that have nothing to do with email. Just plain we
| only serve gmail customers. It's likely also another stricter
| variation of we only serve US customers.
| [deleted]
| nicbou wrote:
| The pitch could use a bit of work. I had to muster a lot of
| willpower to read all those paragraphs to figure out what the
| product even does. It would greatly benefit from more
| straightforward writing.
|
| When I clicked, I hoped that it could manage the tedium of
| dealing with emails:
|
| - Negotiating meeting dates and adding events to my calendar.
|
| - Combining pointless corporate emails into an executive summary,
| or deleting them as they come.
|
| - Surfacing metadata when appropriate: the phone number of the
| person I should call, directions to a mentioned place, profiles
| of mentioned people.
|
| A good executive assistant gets stuff out of the way. They reduce
| friction and let you focus on work that matters. "You have to be
| in Frankfurt? Here are your tickets. You are checked in. A taxi
| will pick you up in the afternoon. Your hotel is booked. I sent
| the address to your phone". There is so much low-level tedium
|
| To me, this tool feels like ChatGPT with access to my emails. You
| still have to converse with it, ask it specifically for what you
| want. Instead of magically sorting the things I don't want to
| deal with, it handles the thing _I_ should be dealing with:
| working with other humans.
| [deleted]
| mayop100 wrote:
| There's definitely more we want to do here - including
| prompting you proactively in helpful ways. This is our v1 --
| stay tuned for v2 :)
| [deleted]
| khaki54 wrote:
| I know it's unrealistic, but I wish this were a local appliance I
| could buy. Maybe plug into Home Assistant too.
|
| Sending all my data off to two external services might be a
| bridge too far for me... Then again, I don't trust Microsoft or
| Google either.
| mayop100 wrote:
| [Co-founder of Shortwave here] I know a lot of folks are
| launching "AI Assistants" right now - but ours isn't just a "chat
| with your PDF" thin shim on GPT4. We've got some serious
| infrastructure behind this.
|
| Here are some notes on our architecture:
|
| - We use LLMs at multiple places to choose what data to pull at
| each step. We use an additive approach rather than a chaining
| approach to avoid error propagation. We use GPT3.5-turbo with a
| bunch of hand-rolled prompts for most of this.
|
| - We're using InstructorXL + Pinecone running on GCP for vector-
| based search. We combine this with more traditional search
| methods backed by Postgres & Elasticsearch, to give the assistant
| the ability to fast searches of multiple types. We use a
| x-encoding model trained on open source Q&A data from Bing for
| scoring & reranking to allow us to combine multiple data sources
| and determine what makes the most sense to feed into the final
| prompt.
|
| - We hand-rolled a bunch of rule-based algorithms and heuristics
| on top of the LLMs to deal with email-specific corner cases and
| other issues we couldn't resolve reliably in prompts
|
| - Our user-facing output is generated with GPT4.
|
| This enables a bunch of capabilities that other AI assistants
| can't match:
|
| - Way better search -- Ask a question and get a succinct direct
| answer, including finding emails that would be tough for you to
| find through traditional search (ie. you can't remember a keyword
| to use).
|
| - Scheduling - Since we can dynamically pull in multiple types of
| data, we can access calendar data at the right time to help you
| schedule meetings.
|
| - Analyze across multiple emails & types of data - The assistant
| can synthesize answers across multiple emails, your calendar,
| setting, etc to give you an answer (eg. "What are the top 5
| issues that customers emails support about last week", "what are
| some meeting times that work for me and the other people on this
| thread"),
|
| - Write in your voice -- the assistant can automatically learn
| your style and tone based on your sent emails. This means it
| actually sounds like you and, while it still requires some
| tweaking occasionally, it'll save you a lot of time.
|
| - Summarize & translate - it can dynamically access the data you
| have _on your screen right now_ if you reference it, so it can
| help you with whatever you're reading.
|
| A note on privacy: We take privacy very seriously. We're running
| everything above on our own GPUs + using OpenAI for final
| outputs. We aren't training any models on user data.
|
| We've put a lot of thought and effort into this one - I hope you
| like it - either way, let me know what you think in the comments
| below!
|
| -Andrew
| spdustin wrote:
| Curious about the "Write in your voice" feature. Is it mostly
| derived from LLM stylometry, or do you blend statistical
| approaches like those used by spaCy? Do you capture all of
| lexical, syntactical, rhetorical, and semantic cues? I'd love
| to chat about your approach, if you're open to any
| opportunities for comparing notes!
| mayop100 wrote:
| Right now we use an LLM to extract a textual description of
| your writing style from past emails, and then we use that in
| the prompt.
|
| The nice thing about this is that it's _editable_ , so the
| user can customize the style to be the style they want, not
| necessarily exactly the style they have.
|
| We're also investigating doing per-user model training for
| more refined voice... not launched yet though (and comes with
| tradeoffs).
|
| Happy to swap notes -- email me: andrew@shortwave.com
| charlierguo wrote:
| I honestly think tightly integrating language models with email
| will be one of the most impactful use cases for LLMs in the
| short-term. Email, as a medium, is pretty much nothing BUT
| text, and it's something that I (and probably the average HN
| reader) spend tens of hours on each week.
|
| In trying "write it for me" AI tools, the biggest hurdle is
| always matching my own tone and style - I'm pretty particular
| about my writing, and I kind of hate the default tone that
| ChatGPT and Bard use. It seems like you've put a ton of hard
| work into making sure that isn't the case here.
|
| And the analysis is really a cherry on top - I've been waiting
| for a tool that I can ask "what are the 3 most important
| messages that are unread in my inbox?" Excited to try this out!
| mayop100 wrote:
| Boom! Glad you like it - and thank you for the kind words :)
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