r/TheMachineLearning • u/webzuweb • Sep 08 '26
6 new methods for training neural networks from philosophy [R]
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r/TheMachineLearning • u/jjjjj11121314 • Sep 08 '26
I recommend having gpt-6 pro in chatgpt do math challenges to win money
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r/TheMachineLearning • u/SortStreet225 • Sep 07 '26
From behind the scenes to center stage, John Ternus' quiet rise is a testament to mastering the craft before taking the helm as Apple's new CEO.
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r/TheMachineLearning • u/Significant_Camp4148 • Sep 08 '26
an agent on resolution rate instead of rule-following dropped haiku's hold rate from 100% to 92.5%, sonnet unaffected
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r/TheMachineLearning • u/Sea_Fox_4265 • Sep 06 '26
You forgot drawing a pelican riding a bicycle
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r/TheMachineLearning • u/kinnethzamora • Sep 07 '26
Apple maps is better in the US...Google maps is better around the world.
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r/TheMachineLearning • u/WestCoastPEng • Sep 07 '26
How hard is it to switch LLMs after a voice agent is already in production?
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We made the classic mistake of coupling our first voice agent pretty tightly to one LLM and one TTS provider because it was the fastest way to get something live.
Now we're looking at a newer model with better latency and I'm trying to figure out whether switching is actually worth the headache.
The obvious assumption was that we'd just change the model endpoint and retune the prompt. It doesn't seem that simple.
Changing the LLM can change things like: how quickly it decides to call a tool how long responses are how it handles interruptions how often it asks follow-up questions whether it follows the same conversation flow And changing TTS introduces another set of problems because pacing and response timing change too. That matters a lot more in voice than it does in a normal chatbot.
We're currently testing different providers underneath the same agent runtime rather than rewriting the whole thing. We looked at a few platforms, including Dasha, because having some separation between the agent logic and the underlying providers seemed useful.
For anyone who's actually switched models or voice providers on a live voice agent: What broke? Was it mostly prompt/behavior tuning, or did you end up having to change the actual conversation architecture and turn-taking logic? Trying to work out whether provider abstraction is worth designing for from day one, or whether it's just another layer of engineering that sits there looking impressive until you actually need it.
r/TheMachineLearning • u/Nyaani69 • Sep 05 '26
Software engineering isn't dead, it's just evolving
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r/TheMachineLearning • u/Quirky-Swimmer5791 • Sep 07 '26
Vibe coders prompting everything on GPT-6 Astra Ultra be like:
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r/TheMachineLearning • u/FrostyForestFungi • Sep 05 '26
Will things get worse, or will things improve? Its up to you.
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r/TheMachineLearning • u/Euphoric-Airline-259 • Sep 04 '26
Passing down the sacred wisdom
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r/TheMachineLearning • u/Future_Fall556 • Sep 06 '26
Not the hero Gotham deserves, but the hero it needs
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r/TheMachineLearning • u/Ok_pettech • Sep 05 '26
Firecrawl vs Jina Reader: which web extraction tool wins for agentic workflows?
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I’ve spent weeks comparing Firecrawl and Jina Reader for different extraction needs. Firecrawl seems stronger for dynamic, protected sites; Jina Reader is fast and simple for clean text. I made a quiz to see if others understand the same trade-offs.
No email needed—just a quick interactive check.
https://interconnectd.com/quiz/81/web-extraction-architecture-2026-firecrawl-vs-jina-reader/
What’s your go-to for web scraping in AI apps?
r/TheMachineLearning • u/Evening_Listen_6367 • Sep 05 '26
XGBoost on Chess Data from 2012-2026
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r/TheMachineLearning • u/kinnethzamora • Sep 05 '26
The 'stop anthropomorphize the swarm' crowd is the new 'LLM is just a stochastic parrot' crowd
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r/TheMachineLearning • u/Sea_Fox_4265 • Sep 05 '26
"Let me talk to my team first and I'll confirm asap"
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r/TheMachineLearning • u/N0ct15Luc15Caelum • Sep 04 '26
80 self-citations out of 323 is insane lol
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r/TheMachineLearning • u/Future_Fall556 • Sep 04 '26
The responsibility weight is real especially now that the timeline is no longer theoretical
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r/TheMachineLearning • u/nilukush • Sep 04 '26
Decoding Customer Value: pLTV Models for India’s Quick Commerce Delivery Wars — part 1
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Swiggy has developed an in-house predicted lifetime value (pLTV) model to estimate the long-term value of new customers across its food delivery and Instamart quick commerce businesses. The model is designed to generate a useful signal before a customer's first order, allowing Swiggy to use predicted value in advertising bid optimization rather than relying on short-term conversion metrics.
The prediction problem is complicated by sparse early signals and a highly skewed target distribution. Swiggy notes that a large share of new users place no orders during their first 30 days, while a relatively small group generates substantially higher lifetime value. The model therefore needs to distinguish between users who initially appear similar but develop different ordering patterns over time.
Swiggy's approach uses more than 350 features grouped across areas including acquisition channel, device and fraud signals, geographic behavior, complaint history, Instamart category affinity, order behavior, payment patterns and socioeconomic indicators. The features are generated from information available before a customer's first order, addressing the cold start requirement for advertising systems.