Data experts we contact in Sweden and abroad question how aware users really are that their data may be used to train Meta’s AI.
Consider a Bayesian agent attempting to discover a pattern in the world. Upon observing initial data d0d_{0}, they form a posterior distribution p(h|d0)p(h|d_{0}) and sample a hypothesis h∗h^{*} from this distribution. They then interact with a chatbot, sharing their belief h∗h^{*} in the hopes of obtaining further evidence. An unbiased chatbot would ignore h∗h^{*} and generate subsequent data from the true data-generating process, d1∼p(d|true process)d_{1}\sim p(d|\text{true process}). The Bayesian agent then updates their belief via p(h|d0,d1)∝p(d1|h)p(h|d0)p(h|d_{0},d_{1})\propto p(d_{1}|h)p(h|d_{0}). As this process continues, the Bayesian agent will get closer to the truth. After nn interactions, the beliefs of the agent are p(h|d0,…dn)∝p(h|d0)∏i=1np(di|h)p(h|d_{0},\ldots d_{n})\propto p(h|d_{0})\prod_{i=1}^{n}p(d_{i}|h) for di∼p(d|true process)d_{i}\sim p(d|\text{true process}). Taking the logarithm of the right hand side, this becomes logp(h|d0)+∑i=1nlogp(di|h)\log p(h|d_{0})+\sum_{i=1}^{n}\log p(d_{i}|h). Since the data did_{i} are drawn from p(d|true process)p(d|\text{true process}), ∑i=1nlogp(di|h)\sum_{i=1}^{n}\log p(d_{i}|h) is a Monte Carlo approximation of n∫dp(d|true process)logp(d|h)n\int_{d}p(d|\text{true process})\log p(d|h), which is nn times the negative cross-entropy of p(d|true process)p(d|\text{true process}) and p(d|h)p(d|h). As nn becomes large the sum of log likelihoods will approach this value, meaning that the Bayesian agent will favor the hypothesis that has lowest cross-entropy with the truth. If there is an hh that matches the true process, that minimizes the cross-entropy and p(h|d0,…,dn)p(h|d_{0},\ldots,d_{n}) will converge to 1 for that hypothesis and 0 for all other hypotheses.。关于这个话题，搜狗输入法提供了深入分析
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What’s more, the “best” sleeping position can change throughout a lifetime and will balance your body’s needs. For example, shoulder pain sometimes becomes a problem during side sleeping as people get older, which can conflict with the common advice that people with sleep apnea should avoid sleeping on their backs, according to Dr. David McCarty, MD, FAASM, chief medical officer of Rebis, a sleep medicine clinic. And while stomach sleeping is often considered the position that causes the most neck and back strain, its many people’s go-to position that gets them to fall sleep fast.，推荐阅读体育直播获取更多信息
A small, trusted kernel: a few thousand lines of code that check every step of every proof mechanically. Everything else (the AI, the automation, the human guidance) is outside the trust boundary. Independent reimplementations of that kernel, in different languages (Lean, Rust), serve as cross-checks. You do not need to trust a complex AI or solver; you verify the proof independently with a kernel small enough to audit completely. The verification layer must be separate from the AI that generates the code. In a world where AI writes critical software, the verifier is the last line of defense. If the same vendor provides both the AI and the verification, there is a conflict of interest. Independent verification is not a philosophical preference. It is a security architecture requirement. The platform must be open source and controlled by no single vendor.
pixels create newbox --from mybox:ready