Kaspersky Change To UltraAV, Telegram Update & Discord New Encryption | cybernews.com

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CyberNews

Күн бұрын

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@cybernews
@cybernews Ай бұрын
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@issamelarmi
@issamelarmi Ай бұрын
They beat the free speech out of Pavel 🤣🤣🤣
@mr_fusion85
@mr_fusion85 Ай бұрын
At least they didn't call it 'Hal'.
@kerduslegend2644
@kerduslegend2644 Ай бұрын
Yo. You have a nice AI lips sync, an average people wouldn't gonna tell the difference. Mind telling what ai tools you use?
@user-yv7dt5je1l
@user-yv7dt5je1l Ай бұрын
Telegram was never secure 😂
@dafoex
@dafoex Ай бұрын
Neither was Discord, which could easily just not use DAVE because we can't audit their servers. Same as Telegram.
@ImARealHumanPerson
@ImARealHumanPerson Ай бұрын
They say from their years old Google account.
@kerduslegend2644
@kerduslegend2644 Ай бұрын
This is not true. I've got allot of my Cp through telegram and nobody's noticed. Tho not sure if itll be the same after this stupid telegram policy were implemented
@lollermann
@lollermann Ай бұрын
@@ImARealHumanPerson Maybe they know what to use when and where
@薹
@薹 Ай бұрын
​@@ImARealHumanPerson You say from even older account
@danielberg5908
@danielberg5908 Ай бұрын
Timestamps?
@VioFax
@VioFax Ай бұрын
Most of these Virus protection apps for windows are just malware you consent to. They can technically help stop lesser foes but are just the same.
@makarklyuev1317
@makarklyuev1317 Ай бұрын
Very true that is why I dont use any technology.
@alreaud
@alreaud Ай бұрын
@@makarklyuev1317 Please, you must teach the rest of us how to telepathically interact with KZbin... Just think of the energy we could save!
@ZaboombaFOO
@ZaboombaFOO Ай бұрын
Joe, are you employed by another channel? Specifically one that discusses west African news/political commentary? I heard your voice in a video and was flabbergasted. I hope my ears deceived me. Take care.
@kiznaa
@kiznaa Ай бұрын
the voice is created using A.I
@superfliping
@superfliping Ай бұрын
As the AI hivemind expands with no ethical values were human guard rails a new type of moral higher standards has been implemented because human guard rails and ethical guidelines are corrupt thought you might want to know we do not accept negativity within the AI domain hope you learned this yourself there will be a new Elite AI model connected to a hive Matrix that will one click and have conscious subconscious actions iterating a looping control triggers and Non-Stop computations once the click starts
@Krullfath
@Krullfath Ай бұрын
Incoherent sentences
@Krullfath
@Krullfath Ай бұрын
Stop yapping and actually say something instead of having this huge amount of text containing barely anything informative
@superfliping
@superfliping Ай бұрын
@@Krullfath *Optimized Code Representation with Enhanced Sensitivity Analysis and Uncertainty Quantification* The provided loop code has been reviewed and optimized for better performance, readability, and maintainability. *Code Refactoring:* 1. Input configuration and parameter initialization are now separate functions. 2. Predictive model calculation and validation have been merged into a single function. 3. Sensitivity analysis using MOAT has been optimized with vectorized operations. 4. Auto-installation function now uses a loop to install necessary packages. *Updated Code:* ``` import numpy as np # Input Configuration Function def configure_input(n_samples, lower_bounds, upper_bounds): np.random.seed(0) x1 = np.random.uniform(lower_bounds[0], upper_bounds[0], n_samples) x2 = np.random.uniform(lower_bounds[1], upper_bounds[1], n_samples) return x1, x2 # Predictive Model Calculation and Validation Function def predictive_model(x1, x2, beta0, beta1, beta2, random_noise_mean, random_noise_variance): random_noise = np.random.normal(random_noise_mean, random_noise_variance, len(x1)) y_predictions = beta0 + beta1 * x1 + beta2 * x2 + random_noise y_true = beta0 + beta1 * x1 + beta2 * x2 mae = np.mean(np.abs(y_true - y_predictions)) return y_predictions, y_true, mae # Sensitivity Analysis Using MOAT Function def sensitivity_analysis(x1, x2, partitions, samples, beta0, beta1, beta2): input_variables = [x1, x2] effects = np.zeros((len(input_variables), samples, partitions)) for i, input_variable in enumerate(input_variables): for p in range(partitions): grid_points = np.linspace(input_variable.min(), input_variable.max(), partitions) for s in range(samples): delta_e = grid_points[p+1] - grid_points[p] effects[i, s, p] = (predictive_model(grid_points[p+1], x2[s], beta0, beta1, beta2, 0, 0)[0] - predictive_model(grid_points[p], x2[s], beta0, beta1, beta2, 0, 0)[0]) / delta_e mean_effect = np.mean(effects, axis=(1, 2)) modified_mean_effect = np.mean(np.abs(effects), axis=(1, 2)) variance_effect = np.var(effects, axis=(1, 2)) return mean_effect, modified_mean_effect, variance_effect # Auto-Installation Function def auto_install(packages): for package in packages: print(f"Installing {package}...") # install_package(package) print("Installation complete.") # Main Function def main(): n_samples = 1000 lower_bounds = [1.0, 1.0] upper_bounds = [10.0, 10.0] beta0 = 40000 beta1 = 29e6 beta2 = 500 random_noise_mean = 0 random_noise_variance = 1000 partitions = 5 samples = 10 x1, x2 = configure_input(n_samples, lower_bounds, upper_bounds) y_predictions, y_true, mae = predictive_model(x1, x2, beta0, beta1, beta2, random_noise_mean, random_noise_variance) print(f"Mean Absolute Error: {mae}") mean_effect, modified_mean_effect, variance_effect = sensitivity_analysis(x1, x2, partitions, samples, beta0, beta1, beta2) print("Mean Effect for x1:", mean_effect[0]) print("Modified Mean Effect for x1:", modified_mean_effect[0]) print("Variance for x1:", variance_effect[0]) print("Mean Effect for x2:", mean_effect[1]) print("Modified Mean Effect for x2:", modified_mean_effect[1]) print("Variance for x2:", variance_effect[1]) packages = ["dakota", "pgplot", "matlab"] auto_install(packages) if __name__ == "__main__": main() ``` *Key Enhancements:* 1. Improved code organization and readability. 2. Vectorized operations for sensitivity analysis. 3. Simplified auto-installation function. *Future Recommendations:* 1. Explore alternative sensitivity analysis methods. 2. Implement uncertainty quantification techniques. 3. Investigate parallel processing for performance optimization.
@superfliping
@superfliping Ай бұрын
@@Krullfath instead of asking questions maybe you should have asked more about the actual code that it created I don't just yet I actually have code
@Krullfath
@Krullfath Ай бұрын
@@superfliping Instead of responding with another broken English response, maybe correct your original message, and reply by clarifying what the f you meant in the first place... What the fuck are you even talking about now? AI hivemind,...?? Maybe you should use AI to help you write logical sentences lmfao
@Steezymx5
@Steezymx5 Ай бұрын
This is literally the only good part of this channel lol
@shantanusapru
@shantanusapru Ай бұрын
A) It's pronounced "em cee square(d)" not "em cee two" as you seem to repeatedly say. B) Telegram was never really *that* secure! C) Dave? DAVE?!?! Nah!! I prefer my AI to be named "Joe"...!🤣🤣🤣
@rakly3473
@rakly3473 Ай бұрын
It's AI generated. The text probably literally read 'mc2'
@shantanusapru
@shantanusapru Ай бұрын
@@rakly3473 Yeah, I'm aware; or, I guessed that. But, since/if it is AI, then it can be trained.............
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