AI Correction

Extracted Attributes

• Nature

  Market downturn or adjustment

• Beneficiary

  Nvidia

• Primary Trigger

  Significant stock price drop in Salesforce

• Strained Entity

  Dell

• Risk Highlighted

  High costs of AI infrastructure

• Potential Outcome

  Market bubble around AI

• Contributing Factor

  Disruptive influence of generative AI

• Discussion Platform

  The All-In Podcast

• Triggering Event Detail

  Salesforce stock dropped 20%

Timeline

• Salesforce experienced a 20% stock drop, sparking discussion on The All-In Podcast about a potential AI correction and broader market instability. (Source: document_ae452fce-98c8-4d96-a33d-99ffc425bb65)

  Date not specified

Artificial intelligence

Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g., language models and AI art); and superhuman play and analysis in strategy games (e.g., chess and Go). However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore." Various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include learning, reasoning, knowledge representation, planning, natural language processing, perception, and support for robotics. To reach these goals, AI researchers have adapted and integrated a wide range of techniques, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics. AI also draws upon psychology, linguistics, philosophy, neuroscience, and other fields. Some companies, such as OpenAI, Google DeepMind and Meta, aim to create artificial general intelligence (AGI)—AI that can complete virtually any cognitive task at least as well as a human. Artificial intelligence was founded as an academic discipline in 1956, and the field went through multiple cycles of optimism throughout its history, followed by periods of disappointment and loss of funding, known as AI winters. Funding and interest vastly increased after 2012 when graphics processing units started being used to accelerate neural networks and deep learning outperformed previous AI techniques. This growth accelerated further after 2017 with the transformer architecture. In the 2020s, an ongoing period of rapid progress in advanced generative AI became known as the AI boom. Generative AI's ability to create and modify content has led to several unintended consequences and harms, which has raised ethical concerns about AI's long-term effects and potential existential risks, prompting discussions about regulatory policies to ensure the safety and benefits of the technology.

Web Search Results

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  AI is a broad discipline within computer science that encompasses a wide range of methods that seek to create machines that mimic human intelligence. Implementing AI in corrections has the potential to impact a wide range of agency operations that facilitate making decisions and performing tasks; for example, AI technologies can determine whether a pretrial defendant should be detained in jail, facilitate the selection of rehabilitation services suitable for various offender needs, assist in [...] About Contact Us Subscribe Topics A-Z Share Facebook X LinkedIn Reddit Pinterest Email × "Clear search box") 1. Home 2. Library & Multimedia applications in criminal justice, provides an overview of AI applications and considerations for corrections system administrators and policymakers. Abstract [...] lowering the risks of using AI, the importance of high-quality data in developing new AI applications in corrections, and current operational limitations to AI use. 3 figures and 12 references

• What to Know About AI Self-Correction - Lionbridge

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• Free AI Editing - EditMyEnglish

  The AI engine was trained by OpenAI on a vast corpus of high-quality English text, enabling it to recognize and correct common grammar and usage errors, such as misplaced modifiers, subject-verb agreement mistakes, and verb tense inconsistencies. Additionally, the engine can understand the context of a sentence and suggest improvements to sentence structure, word choice, and overall clarity. Image 7 [...] system not only corrects syntax, punctuation, and spelling but also makes changes to enhance clarity, coherence, and style. Whether you're working on essays, research papers, or creative projects, our AI editing tool is the ultimate tool for achieving academic success, and when combined with editing from our expert human editors, we can elevate your writing and unlock your full writing potential. EditMyEnglish is not affiliated with OpenAI. Image 5 #### Paste Your Text To Edit Here [...] While our AI editing tool can greatly enhance the quality of your document, some clients have found that adding a human editing step after using our tool can ensure that their text meets the highest standards of writing.Our human editors can address the more nuanced aspects of writing that may require a human touch, and they can also provide helpful comments that many clients find beneficial. Ultimately, whether you choose to have one of our expert editors review your document after using our

• Error Correction and Adaptation in Conversational AI: A Review of ...

  Error correction is essential for addressing biases in ML models. Biases, often ingrained in the training data, can lead to skewed outcomes, exacerbating existing societal prejudices . Techniques like data augmentation, re-weighting, and adversarial training can help identify and mitigate biases within models . Error correction also plays a crucial role in enhancing a model’s ability to generalize from training data to new, unseen data . As models are deployed, they encounter novel data and [...] feedback, refining the accuracy and relevance of its responses over time. [...] Error correction is an important component of chatbots that shapes their efficacy and reliability. This includes enhancing the chatbot’s learning capabilities, adaptability, and accuracy. ML models, trained on extensive datasets, are designed to identify patterns, make decisions, and predict outcomes. Despite their sophistication, these models are prone to errors due to factors such as biases in training data, overfitting, underfitting, or the complexity of tasks [12,13]. Error correction