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🚨 Who needs a SS? 🚨 Robert Martinez (Robert Anthony Martinez lll) makes it look smooth and effortless at SS! He makes SportsCenter top 10 plays everyday at practice! 👀 Uncommitted SS 85 MPH across inf Batted .366 in 6A senior year! Cell - (972) 799-1210 #TCSteam12
15,144 次观看 • 7 个月前 •via X (Twitter)
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![Some love stories don't end with a goodbye. They simply find a quieter way of staying. For 53 years, SS Mishra and his wife built a life around the smallest rituals — doing yoga together every morning, sharing household chores, remembering each other's favourite breakfast, and finding joy in ordinary days. When she passed away last year, the silence was unbearable. But instead of letting her memories fade, he chose to keep a part of her alive. His wife loved crocheting. Whenever she needed a new colour of wool, it was her husband who would go searching for it. She had once created a page to showcase her work. Hardly anyone noticed it then. Today, after her passing, it's her husband who uploads her crochet creations. Thousands now admire the art she poured her heart into. Sometimes, he looks at the comments and quietly says, "They finally see you. I think you must be smiling from heaven." He still makes the same breakfast they once shared. He still brings home her favourite flowers. Their home is still filled with the cushion covers and table pieces she lovingly crocheted. Because for him, love didn't end the day she left. It simply became something he chooses to live, every single day.❤️ #LoveBeyondLife #TrueLove #SeniorCitizens #CrochetArt #HeartwarmingStories [crochet legacy, lifelong love, grief and healing, human stories, lasting memories]](https://image.24vids.com/tw-2079891707894849545/amplify_video_thumb/2079878556537241600/img/e2JNbyyBZTJmXuZp.jpg)
![In preparation for this, I checked out Dr. Jordan Cooper's (Dr Jordan B. Cooper) video on Chemnitz's examination of traditions and he made the remark that the Catholic Church contradicts the consensus of the Fathers on communion in both kinds, and that there is "no example of" communion in one kind in the Fathers. Respectfully, I think this is a messy critique which misses what is going on at the Reformation and what the precise claim of the Reformers was. I have already made a video extensively citing examples of communion in one kind starting in the 3rd century, through Tertullian, Ss. Jerome, Basil, etc, such as the widespread practice of private communion at home with the Eucharistic bread only. I will link it below. These are usually dismissed as "extraordinary instances," but this only shows that the Fathers did not actually agree with the Reformers. Remember, the Reformers (specifically the Lutheran orthodox) said that communion in one kind can NEVER happen. Johann Adam Scherzer, for example, said that if someone cannot receive wine, “[he] should be kept away from the whole, than that he should not receive the whole” (Anti-Bellarmine, disp. 11, th. 6, obj. 9). To demonstrate that the Catholic Church "contradicts" the Fathers on communion in both kinds (which is Dr. Cooper's internal critique), one needs to show that the Fathers of any age unanimously (at least morally) taught that it was a matter of faith to hold that both kinds must be received. Certainly, no consensus ever existed. On the contrary, we know they often did make the exception and allowed Christians to receive only one kind, which shows they did not agree with the Lutherans that this is a divine precept (to receive both). Dr. Cooper conflates the ordinary liturgical practice with what Catholics mean by a "consensus on the Fathers." For more, I recommend reading St. Robert Bellarmine who has a really good response to Martin Chemnitz. Here is a helpful example. It was truly a unanimous practice to preserve the Eucharist after the liturgy and treat the elements as consecrated. The Reformed (to my knowledge) unanimously deny this is the case, and the Lutherans (from my reading of Chemnitz and Gerhard) admit that Christ's presence persists but only for taking the Eucharist to the sick. The early Church affirmed Christ's presence in the Eucharist in the Catholic sense; they preserved it even for reasons which were not for the sick and nevertheless affirmed its lasting consecration (Ss. Irenaeus, Ambrose, Jerome, to name a few). The Catholic view of tradition tells us that this practice/belief (that Christ is still present post-liturgy) must be valid and true (since the universal church cannot err), but it does not establish a precept i.e. just because the whole Church often preserved the Eucharist, it does not mean we actually have to do it; it just means we can do so validly and licitly; it also means this is a certain rule which Protestants contradicted (from a Catholic POV). Even if communion in both kinds was the universal practice (which it was not), this would not suffice to say the Tridentine Church is in contradiction, since this would only tell us it is valid (duh, so does Scripture). There would need to be a unanimous testimony from the Fathers of, let's say, the fourth century, that communion in both kinds is the only way and that to oppose this is heresy; a testimony which does not exist and is even contradicted.](https://image.24vids.com/tw-2081096782948213085/amplify_video_thumb/2081092202709553152/img/a8TxxtUS50pmGBfu.jpg)
![Vector Database by hand ✍️ ~ 10 steps walkthrough below Vector databases are the backbone of Retrieval Augmented Generation (RAG). How do they actually work? Goal: index three sentences, then answer a query by finding the nearest one, filling in every cell yourself. = 1. Given = A dataset of three sentences, three words each. In practice it is millions of them. = 2. Word embeddings = Let us look up each word in an embedding table. Here the vocabulary is 22 words; in practice it is tens of thousands, and the vectors have thousands of dimensions rather than four. = 3. Encoding = We feed the sequence to an encoder, one linear layer and a ReLU, and get one feature vector per word. In practice the encoder is a transformer. = 4. Mean pooling = Let us average across the columns. Three word vectors collapse into one, which is what people mean by a text embedding or a sentence embedding. = 5. Indexing = We multiply by a projection matrix and the four dimensions become two. It is doing the job of a hash: a short representation that is faster to compare, and it is what gets saved in the vector storage. = 6. Process "who are you" = Let us repeat steps 2 to 5 on the second sentence. = 7. Process "who am I" = We do it a third time. The database is now indexed. = 8. Query "am I you" = Let us push the query through the very same pipeline: lookup, encoder, mean pooling, projection, and it lands as a 2D vector in the same space. = 9. Dot products = We transpose the query and multiply, which takes the dot product against every stored vector at once. The dot product is the estimate of similarity. = 10. Nearest neighbour = Let us scan for the largest: 60/9 beats 44/9 and 40/9, so the answer is "who am I". Scanning billions of vectors one at a time is what makes this the slow step in practice, which is why real databases use an approximate nearest neighbour index like HNSW. The outputs: Stored index vectors = [5/3, 2/3], [5/3, 0], [7/3, 2/3] Query vector = [8/3, 2/3] Dot products = 44/9, 40/9, 60/9 Nearest neighbour = "who am I" The takeaway: a vector database is an embedding pipeline, a projection, and a dot product. Every step here is arithmetic you can do in pen, which is worth remembering when the word "database" makes it sound like something else. 💾 Save this post!](https://image.24vids.com/tw-2081020431767581061/ext_tw_video_thumb/2081020419935449088/pu/img/j0l6wBTIjusWDAaV.jpg)
