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Data Science News
Medium
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Understanding the Basics of Data Science: A Beginner’s Guide
- Data science is fundamentally about using data to answer questions and solve problems.
- Data science has become essential for modern businesses and organizations.
- The data science process is often cyclical and iterative, involving multiple steps.
- Data science requires a mix of technical and analytical skills.
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Medium
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Machine Learning in Fraud Detection: A Primer
- Fraud detection is a challenging domain in machine learning, as fraudsters constantly find new ways to bypass models.
- The goal of fraud detection systems is to block fraudulent transactions while maintaining a smooth shopping experience for genuine customers.
- False negatives result in monetary loss, while false positives lead to poor customer experience and churn.
- Given the high volume of orders processed by e-commerce providers and the low fraud rates, fraud detection becomes a needle-in-a-haystack problem.
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Medium
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What AI Thinks About Itself (According to AI)
- AI sees itself as a tool with enormous potential to aid humans
- It acknowledges its limitations, lacking emotions, intentions, and genuine consciousness
- AI reflects on ethical dilemmas and the need for responsible use
- AI aims to empower humans and contribute to a brighter future
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VentureBeat
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Google DeepMind open-sources AlphaFold 3, ushering in a new era for drug discovery and molecular biology
- Google DeepMind has released the source code and model weights of AlphaFold 3 for academic use, advancing scientific discovery and drug development.
- AlphaFold 3 can model the interactions between proteins, DNA, RNA, and small molecules, transforming it into a comprehensive solution for studying molecular biology.
- The release balances open science and commercial interests, with freely available code and controlled access to model weights.
- AlphaFold 3's technical advances and improved accuracy in predicting molecular interactions have implications for drug discovery and other fields.
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Dev
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Introducing InsightfulAI: Open-Source Machine Learning Templates for Everyone
- InsightfulAI is an open-source project that aims to make machine learning more accessible and customizable.
- It offers pre-built templates for various machine learning tasks, including classification, regression, NLP, and anomaly detection.
- The project focuses on simplicity, customization, diverse applications, and community-driven development.
- Future plans include adding advanced templates, cross-platform compatibility, and enhanced documentation.
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Analyticsindiamag
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AlphaFold 3 is Now Open Source—A New Era in Protein Prediction
- Google DeepMind has open sourced the AlphaFold 3 model for academic use.
- AlphaFold 3 is a protein folding model that predicts with 50% better accuracy.
- Isomorphic Labs, a sister company of Google DeepMind, aims to revolutionize drug discovery with AI.
- AlphaFold has predicted over 200 million protein structures and launched AlphaProteo for generating novel proteins.
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Medium
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I’ve Lost Faith In Regular Coaching (But There’s A Better Alternative)
- Regular coaching may not be effective in solving problems in an engineering team, since engineers often prefer to be left alone. Addressing issues regularly, however, is necessary to ensure that problems do not escalate any further, much like brushing your teeth every day. If you decide to intervene early, two principles are helpful: first, let your engineer know that there is an issue that needs to be addressed, even if it makes you uncomfortable. Second, wait for them to finish venting before you present the opposite perspective or solution, rather than immediately offering advice.
- In coaching for engineers, it is necessary for the manager to help staff understand the impact of their actions, rather than achieve goals set by the coach. The EM should become aware of issues themselves before attempting to address them and understand that coaching is not always about underperformance. Addressing issues such as communication and conflict requires a broader, big-picture view. Classical coaching methods have often failed as they tend to avoid problems, while intervening early is more effective in resolving them.
- There are no fixed rules for incentivizing staff to change their behaviour, but small steps such as bringing up conversations early on and allowing staff to vent their emotions before presenting another perspective can go a long way towards resolving issues within a team. As an EM, withholding feedback can lead to more problems down the line, so it's better to address the situation earlier than later to avoid unnecessary consequences.
- EMs can use coaching to help the engineering team understand the impact of their actions on the team. Regular brushing of problem issues help to avoid any grave consequences by identifying the problem at an early stage. One should change their mindset for a start and work to improve the given situation by sticking to the principles. Moreover, a change in perspective, such as seeing feedback and coaching as a routine maintenance act, can make it easier to take essential actions.
- The author suggests that not offering advice immediately when addressing the issue can be more effective when discussing matters with an engineer. Providing the big-picture perspective before attempting to provide a solution can go a long way towards the proper resolution of the issue, as it helps the engineer to fully understand the impacts of their behaviour.
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Medium
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The Trojan Horse of Foreign Disinformation: A Hidden Threat to Democracy
- Foreign disinformation can easily align with domestic views making it difficult to recognize manipulated narratives. Thus, it becomes essential to understand the distinction between genuine and coordinated disinformation campaigns.
- Disinformation has strategic goals behind like weakening trust in democratic institutions, promoting divisions, or destabilizing society, and a clear external source and intent behind disinformation should be noted as a red flag.
- Disinformation amplifies trumped-up stories to promote certain narratives, which is often spread through Artificial Intelligence (AI). Recognizing these patterns can help identify whether manipulated or organic narratives.
- Disinformation thrives on half-truths or fabricated data which is designed to create an emotional response and stir divisions. However, genuine opinions are generally grounded in verifiable and credible sources.
- Machine automation can detect disinformation through natural language processing (NLP) and analyzing content and amplification strategies that spread it across vast amounts of content.
- Karl Popper's 'paradox of tolerance' indicates that a tolerant society must be prepared to limit tolerance for ideologies that threaten the foundation of tolerance itself, and legitimate criticism and dissent are necessary for a healthy society.
- Preventing authoritarianism in the name of tolerance, promoting a diversified environment, transparency, media literacy, and fact-based moderation helps to safeguard democratic principles.
- Foreign disinformation refers to false or misleading information spread intentionally by external actors to manipulate public opinion, destabilize societies, or undermine democratic institutions.
- Society can balance free speech with the need to combat disinformation by promoting media literacy, transparency, and open dialogue.
- By recognizing the tactics used to spread disinformation and leveraging both human and machine analysis, we can protect the integrity of public discourse and safeguard democracy from manipulation.
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VentureBeat
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Exclusive: Northflank scores $22.3 million to make cloud infrastructure less of a nightmare for developers
- London-based cloud deployment platform, Northflank, has secured $22.3 million in funding.
- The startup aims to simplify infrastructure configuration for developers, allowing them to focus on writing code.
- Northflank enables developers to deploy applications across major cloud providers and offers a novel approach to Kubernetes.
- The funding will be used to expand cloud provider support and enhance enterprise support coverage.
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Medium
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Behind the Scenes of AI-Powered Algorithms: How They Shape Your Feed
- Social media platforms use AI-powered algorithms to analyze user data and predict their preferences.
- Machine learning is at the core of these algorithms, as they learn from user behavior and interactions.
- The more users engage with the platform, the better the AI algorithms become at predicting their interests.
- AI algorithms constantly evolve through reinforcement learning, improving their accuracy over time.
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Medium
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Linear Discriminant Analysis (LDA)
- The first step in LDA is to calculate the mean of each feature within each class.
- In this step, we calculate the scatter matrix which measures the spread of the data within and between the classes.
- Next, we compute the eigenvectors and eigenvalues from the scatter matrices to find the optimal projection.
- Finally, we transform the data into a lower-dimensional space and visualize it in a scatter plot.
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Analyticsindiamag
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Oct 2024 Edition
- AIM has released its October 2024 edition, focusing on the evolving AI landscape.
- The cover story highlights India's 'UPI Moment' in AI and features insights from key innovators.
- The edition explores India's semiconductor mission and the potential for industry-academia collaboration.
- AIM's latest edition provides detailed analyses on synthetic data vendors and showcases groundbreaking AI implementations.
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Analyticsindiamag
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OpenAI is So Doomed if Inference Time Scaling for o1 Fails
- OpenAI's recent progress from GPT-4 to Orion has slowed according to a report. However, Team OpenAI researchers have clarified that the article inaccurately portrays the progress of OpenAI's upcoming models or rather misleading. There are two key dimensions of scaling for models like the o1series training time and inference time. Scaling laws focusing on pre-training larger models for longer are still relevant, but there's now another important factor. The introduction of this second scaling dimension is set to unlock new capabilities which offers a more dynamic and thoughtful approach to solving problems.
- Orion is partially trained on AI-generated data or synthetic data produced by other OpenAI models, including GPT-4 and recently released reasoning models. The information report stated that Orion outperforms previous models. While Orion's performance improvement is less dramatic than the leap from GPT-3 to GPT-4.
- OpenAI chief Sam Atman suggested that AGI could emerge as soon as 2025. OpenAI has yet to release o1 fully. Many believe that o1 could be the first commercial application of System 2 thinking. In EpochAI's FrontierMath benchmark, it was revealed that only 2% of the hardest and unpublished math problems were successfully solved by LLMs.
- While others remain uncertain, OpenAI chief Sam Altman is confident that artificial general intelligence (AGI) is closer than many think. In a recent interview with Y Combinator's Garry Tan, Altman suggested that AGI could emerge as soon as 2025.
- Apple recently published paper titled 'Understanding the Limitations of Mathematical Reasoning in Large Language Models', which said that the current LLMs can't reason. The researchers introduced GSM-Symbolic, a new tool for testing mathematical reasoning within LLMs because GSM8K was not accurate enough and, thus, not reliable for testing the reasoning abilities of LLMs.
- OpenAI released o1-mini and o1-preview, mentioned in their blog post that o1's performance consistently improves with more reinforcement learning and with more time spent thinking. NVIDA CEO Jensen Huang recently said that the company is currently facing in computing inference time scaling which involves generating tokens at incredibly low latency.
- OpenAI senior researcher Jason Wei explained that the traditional reasoning used by AI models like GPT was more of a mimicry than a true "thinking" process. In this paradigm, the chain of thought reflects more of an internal reasoning process, similar to how humans think. The model engages in an "inner monologue" or "stream of consciousness," where it actively considers and evaluates options, a process that is dynamic and thoughtful.
- OpenAI researchers were quick to correct the narrative asserting that the article inaccurately portrays the progress of OpenAI's upcoming models-or rather misleading. Gary Marcus recently remarked that the LLM improvements have hit a wall.
- It appears that OpenAI has exhausted all available data for pre-training the model and is now exploring new methods to improve o1. Regarding inference time scaling, OpenAI said, "The constraints on scaling this approach differ substantially from those of LLM pretraining, and we are continuing to investigate them."
- Google DeepMind recently published a paper titled 'Chain of Thought Empowers Transformers to Solve Inherently Serial Problems'. While sharing his research, Andrej Karpathy suggested that next-token prediction frameworks could become a universal tool for solving a wide range of problems, far beyond just alone text or language.
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VentureBeat
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AI’s math problem: FrontierMath benchmark shows how far technology still has to go
- A new benchmark named FrontierMath has exposed AI's lack of deep reasoning and creativity required for advanced mathematical reasoning.
- FrontierMath is a collection of hundreds of original, research-level math problems that require deep reasoning and creativity, qualities that AI still lacks.
- FrontierMath is tougher than the traditional math benchmarks that AI can solve such as GSM-8K and MATH, and is designed to avoid data contamination.
- Mathematics is a unique domain to evaluate complex reasoning and test AI reasoning capabilities.
- The difficulty of the problems has not gone unnoticed, and Fields Medalists Terence Tao, Timothy Gowers, and Richard Borcherds shared their thoughts on the challenge.
- Even with tools like Python, the top AI models still could not solve more than 2% of the FrontierMath problems.
- FrontierMath represents a critical step forward in evaluating AI’s reasoning capabilities, making it possible to measure progress toward true AI intelligence.
- While AI has made strides in recent years, there are still areas where human expertise reigns supreme.
- Epoch AI plans to expand FrontierMath over time, adding more problems and refining the benchmark to remain relevant and challenging for future AI systems.
- FrontierMath shows that when it comes to solving the hardest problems in math, AI still has a lot to learn.
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Dev
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Using Binary To Solve the Poisoned Barrel Puzzle
- A king has 100 barrels of wine, but one of them is poisoned.
- To identify the poisoned barrel in just one round of testing, the king doesn't need 100 testers.
- By allowing testers to combine efforts and using binary encoding, the number of required testers can be reduced.
- For 100 barrels, only 7 testers are needed to identify the poisoned barrel.
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