Media Landscape Shift - The report highlights the emergence of new media outlets, particularly those aligned with the MAGA movement, gaining prominence and access, including White House press briefings [1][2][5][6] - Traditional media's trust is at an all-time low, leading to a conflation of information with the personalities sharing it, potentially driving the rise of influencers [11][12] - The report suggests a shift in public perception, with individuals seeking information from trusted personalities rather than corporate newsrooms, indicating a move towards more personalized news consumption [12] Bias and Objectivity in Reporting - The report questions the objectivity of mainstream media, suggesting that all sources, including War Room, operate with inherent biases [13] - War Room openly acknowledges its bias, arguing for transparency in reporting rather than claiming objectivity [13] - The report implies that "facts" can be subjective and influenced by ideological frameworks [14] War Room's Role and Agenda - War Room views itself as an enforcer of the MAGA agenda, focusing on covering opposition forces to President Trump [7] - The report mentions a 2023 study identifying War Room as a top spreader of misinformation among political and news podcasts [8] - War Room aims to share President Trump's message and adapt the White House to the new media landscape [5]

Cultural Identity & Communication - Accents and dialects significantly influence perceptions of intelligence, socioeconomic status, and personality [1][4][6] - Language shapes cultural understanding, with even small words carrying distinct cultural meanings [1] - Judgments based on accents have historical roots, exemplified by the ancient Greek term "barbaros" [4][5] - Social media is a major driver of accent evolution, leading to convergence across geographical boundaries [9] Linguistic Analysis - Languages possess inherent sound qualities, with some perceived as "sexy" (e g, Spanish) due to open vowels and low vocal placement [1][2] - Perceptions of harshness in languages (e g, German) are often influenced by stereotypes and limited exposure [2][3] Personal & Social Impact - Individuals may alter their accents to fit in or project a certain image [1] - Accents tell a story about a person's background, experiences, and influences [10] - Embracing one's accent can be a powerful statement of identity [11][12]

But why does the legacy media do this?The Rabbit Hole (@TheRabbitHole):The likelihood of legacy media discussing a murderer’s race depends on the murderer’s race.This is why BLM martyrs like George Floyd get endless coverage while cases like Iryna Zarutska are forgotten.The bias is clear: https://t.co/I7dNK48aLo ...

Good afternoon everyone. This talk is about the power of perspective. And let me tell you, it really is powerful.What if I told you that the bombings of Hiroshima and Nagasaki were a good thing. I mean, what a daring and shocking way to start a speech, right. And I bet you at least one person in this room disagrees with me. Let me tell you, neither I nor the person disagreeing with me are wrong.For many Americans in 1945, that day was a day that we'll be proud to remember. They saved lives on both sides, co ...

AI Bias and its Impact - AI systems learn and repeat biases and inequalities present in the world due to being trained on biased data [5] - AI bias can lead to exclusion, such as in hiring processes where AI tools favor certain demographics over others [7][8][10][11] - Lack of representation in AI training data can result in systems that do not accurately recognize or serve all users [15][20] The Importance of Awareness and Critical Thinking - Awareness and AI literacy are crucial for challenging biased AI systems and promoting change [6][23] - Questioning AI responses and outcomes can help break the cycle of reinforcing existing biases [6][18] - Individuals have the power to shape the future of AI by being informed, curious, and unafraid to challenge the systems around them [24] Examples of AI Bias and Exclusion - An AI hiring tool favored men due to being trained on 10 years of resumes primarily from men [7][9] - Facial recognition systems have difficulty accurately detecting darker-skinned and female faces [20] - Voice recognition systems may not be trained to recognize higher-pitched voices, excluding women [15] Call to Action - Individuals should understand the biases rooted within technology to question and challenge outcomes [18] - Promoting ethical and equitable AI systems requires collective effort and awareness [22] - The goal is to lead AI and the world towards a future that is fair, inclusive, and human-centered [25]

Core Message - The speech emphasizes the importance of shifting perspective to change lives and the lives of those around us [1] - It advocates for checking biases rather than suppressing them, urging reflection on feelings and assumptions [5][6] - The speaker shares a personal story of homelessness to illustrate how perspective shapes understanding and judgment [9][10] - The speech highlights that homelessness is a condition, not a stereotype, and encourages empathy and understanding [12] Personal Experience & Transformation - The speaker recounts experiencing homelessness at age 16 after a conflict with family [10] - The speaker details overcoming homelessness, graduating high school, and eventually becoming a police officer [11] - The speaker emphasizes the role of support systems, resources, and personal determination in achieving success [11] Social Commentary & Call to Action - The speech challenges the audience to reconsider their judgments of others, particularly those experiencing homelessness [8][9] - It encourages gratitude for one's own circumstances and a focus on the present rather than constantly wanting more [12][14] - The speaker advocates for being a "good neighbor," lifting others up, and avoiding quick judgments [14][15]

Bias in Academic and Media Reporting - Academic and journalistic reporting may exhibit bias by highlighting studies showing bias against women while downplaying or ignoring studies that do not [1] - This selective reporting can lead to a distorted understanding of scientific findings [1]

[Music] [Applause] I would want to start by asking you all a small favor. Could you all just close your eyes. And imagine that you are an 11 years old child again.You're sitting in a chair that is too small to fit your growing body in a classroom that smells like freshly cooked pasta. You check the clock and think, "Oh, okay. I'm half an hour away of this muffin mom promised to give you." You're supposed to be make drawing attention, but no, you you're daydreaming. You're doodling, drifting away, drawing a ...

LLM Security Challenges - LLMs face adversarial attacks via prompts, requiring focus on security beyond correctness, faithfulness, and factual accuracy [1] - A well-crafted prompt can lead to PII leakage, bypassing safety filters, and generating harmful content [2] - Red teaming is core to model development, demanding SOTA adversarial strategies like prompt injections and jailbreaking [2] Red Teaming and Vulnerability Detection - Evaluating LLM responses against PII leakage, bias, toxic outputs, unauthorized access, and harmful content generation is crucial [3] - Single-turn and multi-turn chatbots require different tests, focusing on immediate jailbreaks versus conversational grooming, respectively [3] - DeepTeam, an open-source framework, performs end-to-end LLM red teaming, detecting 40+ vulnerabilities and simulating 10+ attack methods [4][6] DeepTeam Framework Features - DeepTeam automatically generates prompts to detect specified vulnerabilities and produces detailed reports [5] - The framework implements SOTA red teaming techniques and offers guardrails to prevent issues in production [5] - DeepTeam dynamically simulates adversarial attacks at run-time based on specified vulnerabilities, eliminating the need for datasets [6] Core Insight - LLM security is a red teaming problem, not a benchmarking problem; thinking like an attacker from day one is essential [6]

You can't hate the media enough.Wikipedia is the most biased article resource!Grokipedia is actually truth-seeking and unbiased.Anything to paint Elon Musk as a racist will get clicks.X is the only place I come to for truthful news. https://t.co/IZFdYeTLCw ...