Top Tweets for #MeenaBot
This study showed it matters which datacenter is used, even within the same organization. Our #MeenaBot was most expensive to train within Google: took 84 accelerator years, carbon emission ~ 1/2 of a round trip flight SF-NY, but Evolved transformer helped saved 48tCO2 (30%)!
A thorough study of CO2 emissions linked to large neural net training from Google.
It focuses on Google's NLP models & computing infra.
But an equivalent study at FB would yield similar results.
Patterson & al: "Carbon Emissions and Large NN Training"
https://t.co/9yRgOy8KsU
On behalf of the entire Google Research & @GoogleAI communities, I'm excited to share an overview of some of our research in 2020.
Thanks to everyone who helped make this work possible!
https://t.co/EYVeQ7PfO4
Nice progress from FB! Glad to see that #MeenaBot has motivated further research into training chatbots at scale: now Blender is up to 9.4B params. Though not a direct apple-to-apple comparison, Blender seems to excell in engagingness & humanness. Paper: https://t.co/3oeUuPVXBh.
Really proud to announce the open source release of Blender by @facebookai. The largest ever open-domain chatbot which feels more human than any other bot according to human evaluators. Looking forward to what the AI community can build on top of it! https://t.co/YX0ZGRMZbE
A nice set of NLP papers including our own ELECTRA efficient pretraining (https://t.co/mMyV7VXXsI) and #MeenaBot (https://t.co/MsicCdRD9J). Many cool lines of research and I am particularly amazed by advances on Information Retrieval!
NLP Research Highlights — Issue #1
ICYMI, in this article I highlight some NLP trends and topics with a focus on summarizing the what, how, and why of a selection of interesting and important NLP papers published in the last few months.
https://t.co/I4zB4VH8Xg
sample-and-rerank as proposed in #MeenaBot (https://t.co/5G6aiaRlkE) is a simple strategy that gives both diversity and quality for the generation, especially if your model has low perplexity!
The 101 for text generation! 💪💪💪
This is an overview of the main decoding methods and how to use them super easily in Transformers with GPT2, XLNet, Bart, T5,...
It includes greedy decoding, beam search, top-k/nucleus sampling,...: https://t.co/E40KOeIImd by @PatrickPlaten
What's the difference between recent works in semi-supervised learning? Key: consistency training (UDA, FixMatch, ReMixMatch, ICT, etc.) and self-training (#NoisyStudent), see photo below and my recent talk (https://t.co/DBTQH2xHHL with bonus slides on #MeenaBot!).
Interesting read, #MeenaBot are we there yet? Not quite, but this is an impressive step forward! - "Meena scored 79% SSA, Mitsuku and Cleverbot 56%, DialoGPT 48%, and XiaoIce 31%.[.. ] Google measured the average human SSA at 86%" https://t.co/uYfP9fLaOH via @venturebeat
My deep doubts about #MeenaBot value:
"The big issue I see is that Meena's text predictions are almost unpredictable, just because outcomes are generated from statistically trained corpora."
linkedin thread:
https://t.co/jJowFWWXSl
#DialogFlow #ConversationalAI #openDomains
😓I have an idea about what #GoogleAssistant should be.
#Google #GoogleSearch #VoiceSearch #ConversationalAI #ToGetThingsDone #Automation #PersonalAssitants #VoiceAssitants #chatbots #voicefirst
About #MeenaBot data (asked by @GaryMarcus & others):
1. Only one occurrence of "Hayvard" in the training data.
2. The sentence that contains "Hayvard" has meaning similar to "Guess what, I obtained my bachelor from Hayvard."
3. No occurrence of "cow*" in the same conversation.
@xpearhead @lmthang My favorite conversation is below. The Hayvard pun was funny but I totally missed the steer joke at the end until it was pointed out today by @Blonkhart
I found out today that a chatbot can make better jokes than I can 😩 #MeenaBot
@xpearhead @lmthang My favorite conversation is below. The Hayvard pun was funny but I totally missed the steer joke at the end until it was pointed out today by @Blonkhart
#MeenaBot weakeness:
1. comparison with @mitsokubot and Cleverbot is misleading. Apples and oranges! #Mitsuku is a great scripted chatbot made by a single human author (Sir Steve Warswick). #Cleverbot is an old useless game.
2. #MeenaBot is not available for peers reviews.
#Meena
Towards a Conversational Agent that Can Chat About…Anything
The very interesting part for me is the focus on #conversationalAI Human Evaluation Metrics ~ Sensibleness, Perplexity, Personality, Factuality
cc @verena_rieser @catherinebuk @JulianHarris41
#chatbots
I'm perplexed by excitements about overrated #MeenaBot
@bretkinsella ask: "Could this become a conversation engine behind #googleassistant at some point?"
My thoughts: https://t.co/XKogJVZH8R
#crowdsourcing #chatbots #NoConversationalAI #ConversationalAI
Google's New #Meena Chatbot Imitates Human Conversation and Bad Jokes - Voicebot https://t.co/1e6mWmPSY9
@lmthang @quocleix Thanks @lmthang. Great to hear the commitment to #reproducibility. Claims asides, #MeenaBot is really impressive work. Congrats!
@lmthang @an_open_mind @quocleix Congrats on the work with #MeenaBot @lmthang, is there an API where I could use it? (sorry if this was published somewhere but I couldn't find it)
@an_open_mind If this is about #MeenaBot, totally understand the sentiment & we are working hard on making sure the community can verify & reproduce. Our research (cc @quocleix) has always been very open whenever we can. Btw, conversations here are not cherry picked :) https://t.co/rkNykJnun0
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