Google DeepMind’s CEO Says Its Next Algorithm Will Eclipse ChatGPT
JUNE 26, 2023
Demis Hassabis says the company is working on a system called Gemini that will tap techniques that helped AlphaGo defeat a Go champion in 2016.
Algorithmic biases – Is it a challenge to achieve fairness in AI?
Data Science Dojo
SEPTEMBER 7, 2023
Just like people, Algorithmic biases can occur sometimes. AI algorithms are used to make decisions about everything from who gets a loan to what ads we see online. However, AI algorithms can be biased, which can have a negative impact on people’s lives. Thinking why? Well, think of AI as making those characters.
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Why Businesses Should Embrace Machine Learning
Dataconomy
AUGUST 11, 2017
In 2016, Google’s net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn’t stop at any given point; it keeps.
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Speaker Spotlight: Q&A With Dr. Stefan Kühn – Data Natives Berlin 2016
Dataconomy
AUGUST 26, 2016
Together with his team he is developing robust, fast and intelligent algorithms and is applying modern machine learning methods for analyzing large datasets. The post Speaker Spotlight: Q&A With Dr. Stefan Kühn – Data Natives Berlin 2016 appeared first on Dataconomy.
Data Literacy for Responsible AI: Algorithmic Bias
DataRobot
AUGUST 16, 2021
But as the technology’s popularity grows, a number of concerning examples have emerged of AI models operating with algorithmic bias. Algorithmic bias can appear in both supervised and unsupervised AI models. Algorithmic bias can appear in both supervised and unsupervised AI models.
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Amazon Buy Box lawsuit: Serious overpricing claims
Dataconomy
FEBRUARY 13, 2024
All details about the Amazon Buy Box lawsuit This class-action suit focuses on the manipulation of Amazon’s “Buy Box” feature, where an item’s page includes a “Buy Now” or “Add to Cart” prompt, purportedly driven by a biased algorithm.
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Compressing graphs and indexes with recursive graph bisection (2016)
Hacker News
JUNE 23, 2024
We design and implement a novel theoretically sound reordering algorithm that is based on recursive graph bisection. (KDD 2009) for graph compression, and show how it can be employed for compression-friendly reordering of social networks and web graphs and for assigning document identifiers in inverted indexes.
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Groq sparks LPU vs GPU face-off
Dataconomy
FEBRUARY 26, 2024
Recall the historic Go match in 2016 , where AlphaGo defeated the world champion Lee Sedol ? This attribute is particularly beneficial for algorithms that thrive on parallelization, effectively accelerating tasks that range from complex simulations to deep learning model training.
NIST Announces Post-Quantum Cryptography Standards
Hacker News
AUGUST 13, 2024
NIST’s competition for the best quantum-safe algorithm NIST announced a public competition for the best PQC algorithm back in 2016. Since then, NIST has gone through 4 elimination rounds, finally whittling the pool down to four algorithms in 2022. People have tried hard to break this algorithm.
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How to Ensure AI Models Reflect the Richness of Human Diversity
Towards AI
MARCH 22, 2024
I am fascinated by websites like fivethirtyeight.com, — I spent hours glued to their polling and predictive statistics leading up to the 2016 and 2020 US elections (boy, they sure got it wrong in 2016, eh?). Isn’t AI just great for this sort of analysis?
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Counting shots, making strides: Zero, one and few-shot learning unleashed
Data Science Dojo
DECEMBER 8, 2023
In this approach, the algorithm learns patterns and relationships between input features and corresponding output labels. Traditional learning approaches Traditional machine learning predominantly relied on supervised learning, a process where models were trained using labeled datasets.
Data Science Papers – Summer 2019 edition
Data Science 101
JUNE 3, 2019
Playing Atari with Deep Reinforcement Learning (2013) – A bit older, but a classic in the reinforcement learning literature Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning (2018) – title sums it up Borg, Omega, and Kubernetes (2016) – Kubernetes is widely used and this is one of the early papers Integer (..)
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6 challenges of large language models (LLM)
Data Science Dojo
SEPTEMBER 28, 2023
In 2016, Microsoft launched a chatbot called Tay on Twitter. Read more –> Algorithmic biases – Is it a challenge to achieve fairness in AI? This involves reviewing training data for biases, diversifying training datasets, and implementing algorithms that reduce biased outputs.
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MuZero: Mastering Go, chess, shogi and Atari without rules
DeepMind
DECEMBER 22, 2020
In 2016, we introduced AlphaGo, the first artificial intelligence (AI) program to defeat humans at the ancient game of Go. Now, in a paper in the journal Nature, we describe MuZero, a significant step forward in the pursuit of general-purpose algorithms.
Big Data: The Technology Behind Retailers Success
Smart Data Collective
SEPTEMBER 7, 2021
In dynamic pricing strategy, algorithms examine competitor’s pricing and inventory current levels and select the best price that allows retail industry players to stay competitive and gain profit. This global coffee brand has increased its revenue by 26% from 2016 to 2019. However, this process can be automated. Source: ELEKS.
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How Did Authorities Identify the Alleged Lockbit Boss?
Hacker News
MAY 13, 2024
NeroWolfe seems to have abandoned all of his forum accounts sometime in 2016. In November 2016, an exploit[.]ru But now, temporarily, until the service is fully automated, we are working using a different algorithm.” The algorithms used are AES + RSA.
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AI For Video Editing Software: Do The Benefits Outweigh The Risks?
Smart Data Collective
JUNE 14, 2019
AI algorithms can handle the video editing process much more quickly. In 2016, this was demonstrated by IBM when they developed a new machine learning algorithm to edit the video footage for the trailer for the upcoming horror film Morgan. IBM programmed its algorithm to look at the cinematography of other movie trailers.
Humans and AI: What Should You Tell Consumers?
DataRobot
JULY 29, 2021
The research paper “ Cooperating with Machines ” describes the results of research into how algorithms can “cooperate with people and other algorithms at levels that rival human cooperation.” The proactive AI system was able to double the level of mutual cooperation it achieved versus the black-box algorithm.
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AI 101: A beginner’s guide to the basics of artificial intelligence
Dataconomy
APRIL 18, 2023
Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures. AI systems use a combination of algorithms, machine learning techniques, and data analytics to simulate human intelligence. What is artificial intelligence?
AI hallucinations: Are AI models like Chat GPT doomed to always hallucinate?
Data Science Dojo
SEPTEMBER 15, 2023
AI hallucinations: When language models dream in algorithms. Inaccuracies span a spectrum, from odd and inconsequential instances—such as suggesting the Golden Gate Bridge’s relocation to Egypt in 2016—to more consequential and problematic scenarios.
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Powering the future: The synergy of IBM and AWS partnership
IBM Journey to AI blog
SEPTEMBER 11, 2023
IBM and AWS have been working together since 2016 to provide secure, automated solutions for hybrid cloud environments. Data is the fuel that powers AI algorithms, enabling them to generate insights, predictions, and solutions that drive businesses forward.
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Data Science Dojo - Untitled Article
Data Science Dojo
DECEMBER 8, 2023
In this approach, the algorithm learns patterns and relationships between input features and corresponding output labels. Traditional learning approaches Traditional machine learning predominantly relied on supervised learning, a process where models were trained using labeled datasets.
7 Mind-Blowing Facts You Didn’t Know About AI
Smart Data Collective
FEBRUARY 3, 2022
This is almost 20 billion more than the previous year and over 50 billion than in 2016. Human error reduction : AI algorithms are often used to predict if an error in processes and operations is going to occur, and when it’s going to occur. They are AI algorithms designed to mimic a network of neurons that we have in our brain.
Interactive Fleet Learning
BAIR
APRIL 6, 2023
This approach is known as “Fleet Learning,” a term popularized by Elon Musk in 2016 press releases about Tesla Autopilot and used in press communications by Toyota Research Institute , Wayve AI , and others. Using this formalism, we can now instantiate and compare IFL algorithms (i.e., allocation policies) in a principled way.
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Big Data Offers New Solutions for Disaster Mitigation Planning
Smart Data Collective
MAY 21, 2019
In 2016, cyber-attacks cost the United States economy between $57 billion and $109 billion. There are several ways that predictive analytics is helping organizations prepare for these challenges: Predictive analytics models are helping organizations develop risk scoring algorithms. Cybersecurity is becoming a greater concern than ever.
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Can Using Deep Learning to Write Code Help Software Developers Stand Out?
Smart Data Collective
FEBRUARY 23, 2023
The learning potential of deep learning was further demonstrated by AlphaGo in 2016 and, today, it is used increasingly to create high level software engineering (SE) tools. Deep learning is achieved when data is run through layers of neural network algorithms.
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We still have so much to learn from nature
Dataconomy
JULY 18, 2023
The Kilobot platform provides researchers with a practical means to study and experiment with swarm robotics algorithms and concepts. Swarm intelligence algorithms are typically decentralized, meaning that they do not require a central controller.
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Introducing NYU Center for Data Science Research Groups
NYU Center for Data Science
JULY 18, 2023
The group was first launched in 2016 by Associate Professor of Computer Science, Data Science and Mathematics Joan Bruna , and Associate Professor of Mathematics and Data Science and incoming CDS Interim Director Carlos Fernandez-Granda with the goal of advancing the mathematical and statistical foundations of data science.
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Machine Learning Automates Online Store Development for Ecommerce Startups
Smart Data Collective
FEBRUARY 4, 2021
Machine learning algorithms make content personalization possible. A post from Wix back in 2016 talks about some of the benefits of their machine learning solutions: “So many people are talking about ‘Artificial Intelligence’ – but what does it mean for website design?
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Reinventing a cloud-native federated learning architecture on AWS
AWS Machine Learning Blog
OCTOBER 10, 2023
Challenges in FL You can address the following challenges using algorithms running at FL servers and clients in a common FL architecture: Data heterogeneity – FL clients’ local data can vary (i.e., Despite these challenges of FL algorithms, it is critical to build a secure architecture that provides end-to-end FL operations.
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Crack Detection in Concrete
Towards AI
JULY 19, 2023
Basically crack is a visible entity and so image-based crack detection algorithms can be adapted for inspection. Deep learning algorithms can be applied to solving many challenging problems in image classification. Deep learning algorithms can be applied to solving many challenging problems in image classification. Adhikari, O.
Eye of the Beholder
O'Reilly Media
APRIL 5, 2023
That’s because AI algorithms are trained on data. And it’s safe to say that most AI algorithms are trained on datasets that are significantly older. In 2016, Microsoft’s Tay chatbot was shut down after making racist and sexist comments. By its very nature, data is an artifact of something that happened in the past.
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13 Biggest AI Failures: A Look at the Pitfalls of Artificial Intelligence
Pickl AI
APRIL 8, 2024
This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. From the moment we wake up to the personalized recommendations on our phones to the algorithms powering facial recognition software, AI is constantly shaping our world.
"Only by embracing AI can you be involved in controlling it" says LookX founder Wanyu He
JULY 14, 2023
Wanyu He co-founded the company in Shenzhen in 2016 under the name Xkool, along with former Google senior engineer Chun Li and crossover designer Xiaodi Yang. LookX develops algorithms to quickly generate, evaluate, and recommend schemes for architects that take account of local regulatory requirements while providing real-time cost analysis.
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The Hidden Cost of Poor Training Data in Machine Learning: Why Quality Matters
How to Learn Machine Learning
OCTOBER 10, 2024
Training data is the data you use to train an algorithm or machine learning model The quality of this data has a great impact on the model’s subsequent development, setting a powerful precedent for all future applications that use the same training data. Machine learning algorithms rely heavily on the data they are trained on.
Faster R-CNNs
PyImageSearch
NOVEMBER 13, 2023
One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Since then, the R-CNN algorithm has gone through numerous iterations, improving the algorithm with each new publication and outperforming traditional object detection algorithms (e.g.,
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Technical Analysis is Changing Quickly in the Era of Big Data
Smart Data Collective
JULY 16, 2023
For example, due to computerization and algorithmic trading, Goldman Sachs decreased the number of people trading stocks from 600 to 2, from 2000 to 2016. Emotions, one of the biggest pitfalls of a trader, are eradicated as algorithmic trading takes the stage.
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85 How Big Data Has Impacted The Real Estate Industry
Smart Data Collective
MARCH 22, 2019
In 2016, household incomes rose enough for families to buy a home that was 1.5 They will be even better at this in the future, as big data algorithms improve further. The error rate for real estate professionals using AI algorithms is just 9%. times the median home price. Accurate Property Evaluations.
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77 How Big Data Is Transforming Social Media Marketing
Smart Data Collective
SEPTEMBER 13, 2019
The Guardian mentions the scandal, where analytics research group Cambridge Analytica is reported as harvesting millions of users’ data to influence the 2016 election outcome. define social media mining as a series of algorithms and concepts that can be used to investigate the massive amount of data contained in social media.
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Machine Learning Is Quickly Rewriting The Rules For SEO Link Building
Smart Data Collective
AUGUST 12, 2019
Google is constantly developing new artificial intelligence algorithms to improve search engine results. John Giannandrea, the head of Google Search that was appointed in 2016, has stated that AI is the biggest disruptor in online search. However, Google isn’t the only company using AI and machine learning in search.
6 Spectacular Reasons You Must Master the Data Sciences in 2020
Smart Data Collective
MARCH 17, 2020
Data Science is a field that extracts useful information from loads of structured and unstructured data using algorithms, statistics, and programming. By 2016, everyone wanted to hire a data scientist, and everyone wanted to be a data scientist. Its primary focus is to use user-generated data to good use. Sexiest Job of 21 st Century.
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Efficient continual pre-training LLMs for financial domains
AWS Machine Learning Blog
MARCH 28, 2024
News CommonCrawl is a dataset released by CommonCrawl in 2016. News CommonCrawl SEC Filing Coverage 2016-2022 1993-2022 Size 25.8 billion words The authors go through a few extra preprocessing steps before the data is fed into a training algorithm. Publicly listed companies are required to file various documents regularly.
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The effectiveness of clustering in IIoT
Mlearning.ai
APRIL 10, 2023
3 feature visual representation of a K-means Algorithm. Essentially, the clustering algorithm is grouping data points together without any prior knowledge or guidance to discover hidden patterns or unusual data groupings without the need for human interference.
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Announcing the Keynote Speakers for ODSC West 2024: Experts from NVIDIA, Google, and More!
ODSC - Open Data Science
OCTOBER 4, 2024
His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and deep reinforcement learning algorithms. His career has spanned both technology and government.
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