我跟Austin的观点类似,大家可以参考,在AI赛道的配置上,我看好几个领域:
1、AI大模型访问的数据隐私,龙头 $VVV ,低市值 $PHA ;
2、训练数据获取,看好 $GRASS ;
3、去中心化计算,推理资源的去中心化, 有 $ATH $IO $AKT 。
外加三大基础设施: $VVV $TAO $NEAR
关于Austin最后一个身份协议我不是很认同,因为收入形式不明确。
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There are 5 core elements of the intersection of AI and crypto that I find most compelling. In no particular order:
1. Consumer AI apps that maintain data privacy
2. Distributed training of AI models comparable to those of the frontier labs
3. Data protocols to support model pretraining
4. Tokenized compute
5. Identity attestation
All of these categories have liquid tokens with demonstrated traction, revenue, and accelerating growth. Very likely in my opinion that they materially outperform the broader market from here
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