Shushant Lakhyani
RT @ChideraSays: It's easier to focus on your weaknesses than your strengths.

For now:

Draw confidence from your strengths.

Work hard on your weaknesses.

Eventually, weaknesses become your strengths

Then repeat, repeat, repeat.
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Jeremy Torman (editions available now!)
Left or Right? https://t.co/3IlB1CKGAk
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Gary Wu
Technical moat for 95% of generative AI 'products' right now is zero. Most of these products are features that can be hacked together in a week.

Market structure for these products will approach perfect competition.
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Robert Scoble
RT @bbrague: Data don't lie... Personality traits drive conversion. If you don't know the personalities of your customers, then you are already playing catch-up. #IYKYK #revops #MarketingStrategy #AI #martech https://t.co/ohsbrucSKt https://t.co/94Y2eLAT23
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The Right To Bear Memes
RT @DavarEchad: https://t.co/ti14ciVWE7
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dave
The chatter around bias in AI seems to be waining. Do you think that's because

1) capabilities have given us something more interesting to think about

2) the tech is maturing vis-à-vis alignment
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proxima centauri b ▫️ open edition live!
RT @cypheristikal: GM Anons 🌀

Since I've received interest from multiple parties on this piece, I will be listing my #phospiral tribute 'Museum Visit' as a 1/1 on @foundation with a 0.1 reserve at 3pm EST.

There will also be a bidder's edition (shown below). https://t.co/SKhMAwWuAh
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Zohaib Ahmed
🎉Introducing Neural Speech Watermarking from @resembleai

PerTh is built for protecting synthetic voices from data manipulation. It embeds imperceptible data into the speech and provides a way to verify genuine content.

Read: https://t.co/0Kz9mVmD1K
Open source soon!
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TomLikesRobots
RT @LiJunnan0409: Can LLMs understand images? We introduce 🔥BLIP-2🔥, a generic and efficient vision-language pre-training strategy that bootstraps from frozen❄️image encoders and frozen❄️LLMs. BLIP-2 outperforms existing SoTAs with only 188M trainable parameters!
Github: https://t.co/vXi6CCID7w https://t.co/q5oKrTzsxh
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