@tlctefomaiqe_12: nhắm mắt cô đơn luông#xh #viral #learnontikok #fyd #tlinh

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Monday 13 October 2025 03:11:06 GMT
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yeu_341
bánh Pocky 🫣 :
xin link áo với ạ
2025-10-13 04:31:02
1
khthuongg_91
t. :
vd này phải xhh😭
2025-10-13 05:08:07
1
nhimdangiu191
Mình rất ko chào bạn! :
Hộ vid như này đc ko ạ
2025-10-19 08:40:16
1
h_btraam
hachiware :
xin in4 ốp với ạ
2025-10-16 01:39:54
0
.haivk.ck3
haivk.ck:3 :
Tim vd mới cho mình đc kh ah 💗💗💗
2025-10-23 15:12:55
0
dung.lam.ton.thuong.t.nx
TA. :
số dư ko đủ để mua hạnh phúc nên chọn 1 mình
2025-10-15 13:12:37
0
ngc.th239
mèo🐱🐱 :
hộ vd đầu với ạ
2025-10-14 16:11:13
0
gialinhxinhgai4
glinh chuchee💗>< :
hộ vd ms đăng dớii ạ
2025-10-15 11:14:46
0
duongduongcte02
Anh Duong :
@Linh hazz
2025-10-15 04:23:57
0
denthuilui_
cu đen :
@minhvyy tốt nhứt
2025-10-19 12:59:42
1
ngkhanhlinhh20
khanh linh :
@huyen my
2025-10-17 05:45:20
1
nhoanhvai.lon
kẹo luffy :
🥰
2025-10-13 12:35:33
1
baoan_han
ng tình mùa hạ :
@𐙚𝒯𝒽𝒶𝓃𝒽 𝒰𝓎ê𝓃 vừa đau vừa đắt
2025-10-13 10:39:39
1
mihchau3105
myh.chau ᰔᩚ :
@only_dlingg mình co bạnn yêu màaa
2025-10-22 15:02:13
0
mie_thwg
Mai Thuong :
😏
2025-10-15 13:24:23
0
tranvanphuc56
phúc Trần 🪾 :
đắng cay mặn ngọt tao đã chịu😅
2025-10-16 06:05:02
0
no.c.ny.i.tn5382
Boyy Thủ Môn 🧤⚽ :
vgggggg hzz
2025-10-15 14:33:28
0
raplenhe
Trăm Anh :
em đừng phát biểu nữa bây bi à
2025-10-13 03:18:48
1
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Demystifying AI: A Glossary of Key Terms Artificial intelligence (AI) is rapidly transforming our world, impacting everything from healthcare and finance to entertainment and transportation. Yet, the terminology surrounding AI can often feel opaque. This glossary aims to bridge that gap by providing clear and concise explanations of essential AI terms for the IT professional. Core Concepts: Artificial Intelligence (AI): The ability of machines to exhibit human-like intelligence, including learning, reasoning, problem-solving, and decision-making. Machine Learning (ML): A subfield of AI where algorithms learn from data to improve their performance on a specific task without explicit programming. Deep Learning: A subset of ML inspired by the structure and function of the human brain, utilizing artificial neural networks to process complex data. Data and Learning: Algorithm: A set of instructions that a computer follows to perform a specific task. In AI, algorithms are often trained on data to learn and improve. Training Data: Labeled data used to train an AI model. The quality and quantity of data significantly impact the model's performance. Supervised Learning: A type of ML where data is labeled with the desired output, allowing the model to learn the relationship between inputs and outputs. Unsupervised Learning: A type of ML where data is unlabeled, and the model identifies patterns or structures within the data itself. Model Performance: Accuracy: The proportion of correct predictions made by an AI model. Bias: A systematic preference for or against a particular outcome, which can negatively impact the fairness and reliability of an AI model. Explainability (XAI): The ability to understand how an AI model arrives at its decisions, crucial for building trust and ensuring ethical use. Applications: Natural Language Processing (NLP): Enables computers to understand and process human language, used in applications like chatbots and machine translation. Computer Vision: Equips machines with the ability to extract meaning from visual data, used in tasks like image recognition and object detection. Robotics: Combines AI and engineering to create intelligent robots capable of interacting with the physical world. By understanding these key terms, IT professionals can better navigate the ever-evolving field of AI and leverage its potential to enhance various aspects of their work.
Demystifying AI: A Glossary of Key Terms Artificial intelligence (AI) is rapidly transforming our world, impacting everything from healthcare and finance to entertainment and transportation. Yet, the terminology surrounding AI can often feel opaque. This glossary aims to bridge that gap by providing clear and concise explanations of essential AI terms for the IT professional. Core Concepts: Artificial Intelligence (AI): The ability of machines to exhibit human-like intelligence, including learning, reasoning, problem-solving, and decision-making. Machine Learning (ML): A subfield of AI where algorithms learn from data to improve their performance on a specific task without explicit programming. Deep Learning: A subset of ML inspired by the structure and function of the human brain, utilizing artificial neural networks to process complex data. Data and Learning: Algorithm: A set of instructions that a computer follows to perform a specific task. In AI, algorithms are often trained on data to learn and improve. Training Data: Labeled data used to train an AI model. The quality and quantity of data significantly impact the model's performance. Supervised Learning: A type of ML where data is labeled with the desired output, allowing the model to learn the relationship between inputs and outputs. Unsupervised Learning: A type of ML where data is unlabeled, and the model identifies patterns or structures within the data itself. Model Performance: Accuracy: The proportion of correct predictions made by an AI model. Bias: A systematic preference for or against a particular outcome, which can negatively impact the fairness and reliability of an AI model. Explainability (XAI): The ability to understand how an AI model arrives at its decisions, crucial for building trust and ensuring ethical use. Applications: Natural Language Processing (NLP): Enables computers to understand and process human language, used in applications like chatbots and machine translation. Computer Vision: Equips machines with the ability to extract meaning from visual data, used in tasks like image recognition and object detection. Robotics: Combines AI and engineering to create intelligent robots capable of interacting with the physical world. By understanding these key terms, IT professionals can better navigate the ever-evolving field of AI and leverage its potential to enhance various aspects of their work.

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