In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans. Understanding the semantics of a text is symbol grounding: if language is grounded, it is equal to recognizing a machine-readable meaning. For the restricted domain of spatial analysis, a computer-based language understanding system was demonstrated. Latent semantic analysis (LSA), a class of techniques where documents are represented as vectors in a term space. A prominent example is probabilistic latent semantic analysis (PLSA). Latent Dirichlet allocation, which involves attributing document terms to topics. n-grams and hidden Markov models, which work by representing the term stream as a Markov chain, in which each term is derived from preceding terms. == Stochastic semantic analysis ==
North Atlantic Population Project
The North Atlantic Population Project (NAPP) is a collaboration of historical demographers in Britain, Canada, Denmark, Germany, Iceland, Norway, and Sweden to produce a massive census microdata collection for the North Atlantic Region in the late-nineteenth century. The database includes complete individual-level census enumerations for each country, and provides information on over 110 million people. This large scale allows detailed analysis of small geographic areas and population subgroups. The NAPP database is designed to be compatible with the Integrated Public Use Microdata Series (IPUMS), and is disseminated through the IPUMS data-access system at the Minnesota Population Center, University of Minnesota. Major collaborators on the project include Lisa Dillon, University of Montreal; Chad Gaffield, University of Ottawa; Ólöf Garðarsdóttir, Statistics Iceland; Marianne Jarnes Erikstad, University of Tromsø; Jan Oldervall University of Bergen; Evan Roberts, University of Minnesota; Steven Ruggles, University of Minnesota; Kevin Schürer, UK Data Archive; Gunnar Thorvaldsen, University of Tromsø; and Matthew Woollard, UK Data Archive. The project is also coordinated by the Minnesota Population Center at the University of Minnesota.
How to Choose an AI Resume Builder
Trying to pick the best AI resume builder? An AI resume builder is software that uses machine learning to help you get more done — it scales effortlessly from a single task to thousands. The best picks balance beginner-friendly simplicity with the depth power users need, and they ship updates often. Whether you are a beginner or a pro, the right AI resume builder slots into your workflow and pays for itself fast. This guide breaks down the top picks, their pros and cons, and who each one is best for.
Best AI Headshot Generators in 2026
In search of the best AI headshot generator? An AI headshot generator is software that uses machine learning to help you get more done — it turns a rough idea into a polished result in seconds. When choosing one, weigh output quality, pricing, export formats, and how well it fits the tools you already use. Whether you are a beginner or a pro, the right AI headshot generator slots into your workflow and pays for itself fast. Below we compare features, pricing, and real output so you can choose with confidence.
Noam Slonim
Noam Slonim (Hebrew: נעם סלונים; born in Jerusalem) is an Israeli computer scientist, specializing in Natural Language Processing and the application of Large language models. He is a Research Scientist at Google Research Israel (since September 2025) and formerly an IBM Distinguished Engineer. He founded and served as Principal Investigator of Project Debater and led Language Model Utilization at IBM Research. Beyond his scientific achievements, Slonim had a writing and media career. He was a writer for Season 4 of The Cameric Five TV comedy show, published a weekly column in Haaretz on brain science, and co-created and wrote the Israeli sitcom Puzzle. He was also the head writer for Seasons 2 and 3 of the sitcom Ha-movilim and featured in the 2020 documentary The Debater. In October 2025, his debut novel, Questionable Memories, was published by Kinneret Publishing Group. == Education and research interests == Slonim graduated from the Hebrew University of Jerusalem in 1996 with a B.S. degree in Computer Science, Physics, and Mathematics. In 2002 he completed Ph.D. summa cum laude at the Interdisciplinary Center for Neural Computation at the Hebrew University, under the supervision of Professor Naftali Tishby. His thesis focused on the theory and applications of the Information Bottleneck method. From 2003 till 2006 he did post-doctoral studies at the Lewis-Sigler Institute for Integrative Genomics at Princeton University, working with Professor Bill Bialek and Professor Saeed Tavazoie. He joined IBM Research in 2007. Slonim holds over 30 patents (granted or pending) and has co-authored more than 100 scientific publications. In 2025, he joined Google Research Israel as a research scientist. == Research activities == From 1998 to 2003 he worked on the theory and applications of the Information Bottleneck method, suggesting various cluster analysis algorithms inspired by this method, and demonstrating the practical value of these algorithms on various domains. From 2003 to 2006 he worked on developing Machine Learning algorithms that rely on Information Theory concepts, and applied these algorithms to the analysis of various types of Genomics data. In 2011 he proposed to develop the first Artificial Intelligence system that can meaningfully participate in a full live debate with an expert human debater. This work gave rise to Project Debater, that debated expert human debaters in several live events during 2018 and 2019. In 2020, Slonim delivered the opening keynote at the EMNLP conference, describing the IBM Research work on developing Project Debater. From 2022 to 2025, he led IBM Research efforts applying large language models to practical use cases; in 2025 he moved to Google Research Israel as a Research Scientist. == Writing and video career == In 1996 Slonim was a writer for Season 4 of The Cameric Five TV comedy show. In 1997–1998 he published a weekly column in Haaretz newspaper, focused on brain science research. In 1997–1999 he co-created and co-wrote the Israeli sitcom, Puzzle. In 2008–2010 he was the head writer of Season 2 and Season 3 of the Israeli Sitcom, Ha-movilim. In 2020 he was featured in the documentary The Debater, an official selection of the 2020 Copenhagen International Documentary Film Festival. In 2025, his debut novel, Questionable Memories, was published by Kinneret Publishing Group.
Baby Bundle (app)
Baby Bundle is a parenting mobile app for iPhone and iPad. It was designed to help new parents through pregnancy and the first two years of parenthood. Developed in collaboration with medical experts, it helps track and record the child's development and growth, offers parental advice, manages vaccinations and health check-ups, stores photos and provides baby monitoring services. == History == Baby Bundle was founded in the United Kingdom by brothers, Nick and Anthony von Christierson. Each worked in investment banking prior to developing Baby Bundle, Nick at Greenhill & Co., and Anthony at Goldman Sachs. The idea for the app came when a friend's wife voiced her frustration over having multiple parenting apps on her smartphone. Nick and Anthony left their jobs to create a single app that would include all those features. They conducted market research by interviewing more than 500 parents in the UK and US. It took them a year to build the app, which was named by their mother. Looking for endorsement, they first went to the US in 2013 and partnered with parenting expert and pediatrician Dr. Jennifer Trachtenberg. Baby Bundle was launched in the US and Canadian App Stores in April 2014. In the same month, it became the #1 parenting app in iTunes and was featured by Apple as the #1 Editor's pick across all categories. Mashable called it one of the "Top 5 Can’t Miss Apps." Baby Bundle raised $1.8m seed round in March 2015 to fund development. The money came from a range of angel investors from across the US, UK and Asia. The von Christierson brothers have signed a deal to co-brand the app in the Middle East and expect to launch in Europe and Africa. == Features == Baby Bundle is an app for both the iPhone or iPad and provides smart monitoring tools and trackers for pregnancy and child development. It acts as a growth and daily activity tracker and offers parental advice, manages vaccinations and health check-ups. It has a parenting guide with tips and advice on what to expect when the baby arrives. An interactive forum also lets parents ask questions from others in the community. The app is free and also include paid premium features like the ability to turn two iPhones running into a baby monitor, a cloud service to share the child's data with a spouse and the ability to store data on more than one baby.
ROUGE (metric)
ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics and a software package used for evaluating automatic summarization and machine translation software in natural language processing. The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced) summary or translation. ROUGE metrics range between 0 and 1, with higher scores indicating higher similarity between the automatically produced summary and the reference. == Metrics == The following five evaluation metrics are available. ROUGE-N: Overlap of n-grams between the system and reference summaries. ROUGE-1 refers to the overlap of unigrams (each word) between the system and reference summaries. ROUGE-2 refers to the overlap of bigrams between the system and reference summaries. ROUGE-L: Longest Common Subsequence (LCS) based statistics. Longest common subsequence problem takes into account sentence-level structure similarity naturally and identifies longest co-occurring in sequence n-grams automatically. ROUGE-W: Weighted LCS-based statistics that favors consecutive LCSes. ROUGE-S: Skip-bigram based co-occurrence statistics. Skip-bigram is any pair of words in their sentence order. ROUGE-SU: Skip-bigram plus unigram-based co-occurrence statistics.