The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The U.S. federal funds effective rate underwent a dramatic reduction in early 2020 in response to the COVID-19 pandemic. The rate plummeted from 1.58 percent in February 2020 to 0.65 percent in March, and further decreased to 0.05 percent in April. This sharp reduction, accompanied by the Federal Reserve's quantitative easing program, was implemented to stabilize the economy during the global health crisis. After maintaining historically low rates for nearly two years, the Federal Reserve began a series of rate hikes in early 2022, with the rate moving from 0.33 percent in April 2022 to 5.33 percent in August 2023. The rate remained unchanged for over a year, before the Federal Reserve initiated its first rate cut in nearly three years in September 2024, bringing the rate to 5.13 percent. By December 2024, the rate was cut to 4.48 percent, signaling a shift in monetary policy in the second half of 2024. In January 2025, the Federal Reserve implemented another cut, setting the rate at 4.33 percent, which remained unchanged throughout the following months. What is the federal funds effective rate? The U.S. federal funds effective rate determines the interest rate paid by depository institutions, such as banks and credit unions, that lend reserve balances to other depository institutions overnight. Changing the effective rate in times of crisis is a common way to stimulate the economy, as it has a significant impact on the whole economy, such as economic growth, employment, and inflation. Central bank policy rates The adjustment of interest rates in response to the COVID-19 pandemic was a coordinated global effort. In early 2020, central banks worldwide implemented aggressive monetary easing policies to combat the economic crisis. The U.S. Federal Reserve's dramatic reduction of its federal funds rate - from 1.58 percent in February 2020 to 0.05 percent by April - mirrored similar actions taken by central banks globally. While these low rates remained in place throughout 2021, mounting inflationary pressures led to a synchronized tightening cycle beginning in 2022, with central banks pushing rates to multi-year highs. By mid-2024, as inflation moderated across major economies, central banks began implementing their first rate cuts in several years, with the U.S. Federal Reserve, Bank of England, and European Central Bank all easing monetary policy.

Graph and download economic data for FOMC Summary of Economic Projections for the Fed Funds Rate, Median (FEDTARMD) from 2025 to 2027 about projection, federal, median, rate, and USA.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

View data of the Effective Federal Funds Rate, or the interest rate depository institutions charge each other for overnight loans of funds.

The benchmark interest rate in Brazil was last recorded at 15 percent. This dataset provides - Brazil Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Effective Federal Funds Rate in the United States remained unchanged at 4.33 percent on Thursday July 17. This dataset includes a chart with historical data for the United States Effective Federal Funds Rate.

The benchmark interest rate in Mexico was last recorded at 8 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to May 2025 about savings, personal, rate, and USA.

View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential to revolutionize how we live, work, learn, discover, and communicate. AI research can further our national priorities, including increased economic prosperity, improved educational opportunities and quality of life, and enhanced national and homeland security. Because of these potential benefits, the U.S. government has invested in AI research for many years. Yet, as with any significant technology in which the Federal government has interest, there are not only tremendous opportunities but also a number of considerations that must be taken into account in guiding the overall direction of Federally-funded R&D in AI. On May 3, 2016,the Administration announced the formation of a new NSTC Subcommittee on Machine Learning and Artificial intelligence, to help coordinate Federal activity in AI.1 This Subcommittee, on June 15, 2016, directed the Subcommittee on Networking and Information Technology Research and Development (NITRD) to create a National Artificial Intelligence Research and Development Strategic Plan. A NITRD Task Force on Artificial Intelligence was then formed to define the Federal strategic priorities for AI R&D, with particular attention on areas that industry is unlikely to address. This National Artificial Intelligence R&D Strategic Plan establishes a set of objectives for Federallyfunded AI research, both research occurring within the government as well as Federally-funded research occurring outside of government, such as in academia. The ultimate goal of this research is to produce new AI knowledge and technologies that provide a range of positive benefits to society, while minimizing the negative impacts. To achieve this goal, this AI R&D Strategic Plan identifies the following priorities for Federally-funded AI research: Strategy 1: Make long-term investments in AI research. Prioritize investments in the next generation of AI that will drive discovery and insight and enable the United States to remain a world leader in AI. Strategy 2: Develop effective methods for human-AI collaboration. Rather than replace humans, most AI systems will collaborate with humans to achieve optimal performance. Research is needed to create effective interactions between humans and AI systems. Strategy 3: Understand and address the ethical, legal, and societal implications of AI. We expect AI technologies to behave according to the formal and informal norms to which we hold our fellow humans. Research is needed to understand the ethical, legal, and social implications of AI, and to develop methods for designing AI systems that align with ethical, legal, and societal goals. Strategy 4: Ensure the safety and security of AI systems. Before AI systems are in widespread use, assurance is needed that the systems will operate safely and securely, in a controlled, well-defined, and well-understood manner. Further progress in research is needed to address this challenge of creating AI systems that are reliable, dependable, and trustworthy. Strategy 5: Develop shared public datasets and environments for AI training and testing. The depth, quality, and accuracy of training datasets and resources significantly affect AI performance. Researchers need to develop high quality datasets and environments and enable responsible access to high-quality datasets as well as to testing and training resources. Strategy 6: Measure and evaluate AI technologies through standards and benchmarks. . Essential to advancements in AI are standards, benchmarks, testbeds, and community engagement that guide and evaluate progress in AI. Additional research is needed to develop a broad spectrum of evaluative techniques. Strategy 7: Better understand the national AI R&D workforce needs. Advances in AI will require a strong community of AI researchers. An improved understanding of current and future R&D workforce demands in AI is needed to help ensure that sufficient AI experts are available to address the strategic R&D areas outlined in this plan. The AI R&D Strategic Plan closes with two recommendations: Recommendation 1: Develop an AI R&D implementation framework to identify S&T opportunities and support effective coordination of AI R&D investments, consistent with Strategies 1-6 of this plan. Recommendation 2: Study the national landscape for creating and sustaining a healthy AI R&D workforce, consistent with Strategy 7 of this plan.

The benchmark interest rate in Indonesia was last recorded at 5.25 percent. This dataset provides - Indonesia Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Canada was last recorded at 2.75 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

US Forest Service Forest Inventory and Analysis National Program.

The Forest Inventory and Analysis (FIA) Program of the U.S. Forest Service provides the information needed to assess America's forests.

https://www.fia.fs.fed.us/

Content

As the Nation's continuous forest census, our program projects how forests are likely to appear 10 to 50 years from now. This enables us to evaluate whether current forest management practices are sustainable in the long run and to assess whether current policies will allow the next generation to enjoy America's forests as we do today.

FIA reports on status and trends in forest area and location; in the species, size, and health of trees; in total tree growth, mortality, and removals by harvest; in wood production and utilization rates by various products; and in forest land ownership.

The Forest Service has significantly enhanced the FIA program by changing from a periodic survey to an annual survey, by increasing our capacity to analyze and publish data, and by expanding the scope of our data collection to include soil, under story vegetation, tree crown conditions, coarse woody debris, and lichen community composition on a subsample of our plots. The FIA program has also expanded to include the sampling of urban trees on all land use types in select cities.

For more details, see: https://www.fia.fs.fed.us/library/database-documentation/current/ver70/FIADB%20User%20Guide%20P2_7-0_ntc.final.pdf

Fork this kernel to get started with this dataset.

Acknowledgements

https://www.fia.fs.fed.us/

https://cloud.google.com/blog/big-data/2017/10/get-to-know-your-trees-us-forest-service-fia-dataset-now-available-in-bigquery

FIA is managed by the Research and Development organization within the USDA Forest Service in cooperation with State and Private Forestry and National Forest Systems. FIA traces it's origin back to the McSweeney - McNary Forest Research Act of 1928 (P.L. 70-466). This law initiated the first inventories starting in 1930.

Banner Photo by @rmorton3 from Unplash.

Inspiration

Estimating timberland and forest land acres by state.

https://cloud.google.com/blog/big-data/2017/10/images/4728824346443776/forest-data-4.png" alt="enter image description here"> https://cloud.google.com/blog/big-data/2017/10/images/4728824346443776/forest-data-4.png

The characteristics of food ingested by a primate affect its assimilation of energy by modulating food passage rate. In general, digestive time increases in folivorous primates and decreases in frugivorous primates when they are fed higher fiber diets but this relationship is understudied in exudativorous primates.We compared the food passage rate of five slow loris species.We studied 34 wild-caught slow lorises (15 Nycticebus coucang, 15 N. javanicus, and 4 N. menegensis) in an Indonesian rescue center and four captive-born slow lorises (2 N. bengalensis and 2 N. pygmaeus) in aUK institution. We fed the Indonesian subjects two different diets: a captive-type diet comprising fruits, vegetables, and insects and a wild-type diet formulated to be similar in nutrients to that consumed by slow lorises in the wild, consisting of gum, insects, vegetables, and nectar. We fed the UK subjects a diet of gum, vegetables, insects, and hard-boiled eggs. We formulated this diet to mimic the wild diet, with notably higher fiber fractions and lower soluble sugars than the previous diet. We measured two variables: the transit time (TT) and the mean retention time (MRT). We mixed 1 tsp. of glitter in bananas or gum as our markers and fed them to the slow lorises immediately before their main diet. We noted the date and time of feeding and of appearances of the marker in feces. We weighed food given and left over for each individual to calculate ingested foods and nutrients. We found that TTs were not affected by diet treatment but MRTs were significantly longer for all species fed the wild-type diet. Our results show that Nycticebus spp. have long MRTs for their body weight, and N. pygmdaeus may have the slowest MRT of all primates in relation to body mass. The digestive flexibility of exudativorous primates should allow them to maximize fermentation opportunities when they ingest more (appropriate) fiber by increasing the amount of time the fiber substrate stays in the large intestine. Exudativorous primates appear to have plastic digestive strategies that may be an adaptation to cope with relatively nutrient-poor staple food sources such as gum. The provision of gum in a captive setting may therefore provide benefits for gut health in slow lorises. International Journal Primatology, Vol. 38. Hal. 900-913

Inflation Rate in the United States increased to 2.70 percent in June from 2.40 percent in May of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Russia was last recorded at 20 percent. This dataset provides the latest reported value for - Russia Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.