Testing The Strong Ones
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How I wish author and journalist Sara Hammel had found a stellar editor and publisher for The Strong Ones: it is a story that deserves to be told and is replete with drama - not only physical tribulations but emotional ones as well.
Part one: the selection of 40-some mostly civilian women in Massachusetts willing to work out vigorously for seven months to see how strong they can become, to see if they can do any job in the military, which, in 1995, is limited in opportunities for women. They dragged and carried heavy loads, ran long distances, jumped higher than they thought they could.
Part three: 25 years later and what happened to the women and to the men who trained them. Where are they now and what have they accomplished - and how do they remember their life-changing experience in the 90s
Its testing the strong onesScaring the beautiful onesIt's holding the loved onesOne last timeIts testing the strong ones(testing the strong ones)Its scarring the beautiful ones(staring the beautiful ones)Its holding the loved onesOne last timeIts testing the strong ones(testing the strong ones)Its scarring the beautiful ones(staring the beautiful ones)Its holding the loved onesOne last timeTesting the strong ones(testing the strong ones)Scarring the beautiful ones(scarring the beautiful ones)Its holding the loved onesOne last time
While there are no clear examples of strong artificial intelligence, the field of AI is rapidly innovating. Another AI theory has emerged, known as artificial superintelligence (ASI), super intelligence, or Super AI. This type of AI surpasses strong AI in human intelligence and ability. However, Super AI is still purely speculative as we have yet to achieve examples of Strong AI.
Deep learning is also a sub-field of machine learning, which attempts to imitate the interconnectedness of the human brain using neural networks. Its artificial neural networks are made up layers of models, which identify patterns within a given dataset. They leverage a high volume of training data to learn accurately, which subsequently demands more powerful hardware, such as GPUs or TPUs. Deep learning algorithms are most strongly associated with human-level AI.
The efficient market hypothesis (EMH) is important because it implies that free markets are able to optimally allocate and distribute goods, services, capital, or labor (depending on what the market is for), without the need for central planning, oversight, or government authority. The EMH suggests that prices reflect all available information and represent an equilibrium between supply (sellers/producers) and demand (buyers/consumers). One important implication is that it is impossible to \"beat the market\" since there are no abnormal profit opportunities in an efficient market.\"}},{\"@type\": \"Question\",\"name\": \"What Are the 3 Forms of Market Efficiency\",\"acceptedAnswer\": {\"@type\": \"Answer\",\"text\": \"The EMH has three forms. The strong form assumes that all past and current information in a market, whether public or private, is accounted for in prices. The semi-strong form assumes that only publicly-available information is incorporated into prices, but privately-held information may not be. The weak form concedes that markets tend to be efficient but anomalies can and do occur, which can be exploited (which tends to remove the anomaly, restoring efficiency via arbitrage). In reality, only the weak form is thought to exist in most markets, if any.\"}},{\"@type\": \"Question\",\"name\": \"How Would You Know If the Market Is Semi-Strong Form Efficient\",\"acceptedAnswer\": {\"@type\": \"Answer\",\"text\": \"To test the semi-strong version of the EMH, one can see if a stock's price gaps up or down when previously private news is released. For instance, a proposed merger or dismal earnings announcement would be known by insiders but not the public. Therefore, this information is not correctly priced into the shares until it is made available. At that point, the stock may jump or slump, depending on the nature of the news, as investors and traders incorporate this new information.\"}}]}]}] Investing Stocks Bonds Fixed Income Mutual Funds ETFs Options 401(k) Roth IRA Fundamental Analysis Technical Analysis Markets View All Simulator Login / Portfolio Trade Research My Games Leaderboard Economy Government Policy Monetary Policy Fiscal Policy View All Personal Finance Financial Literacy Retirement Budgeting Saving Taxes Home Ownership View All News Markets Companies Earnings Economy Crypto Personal Finance Government View All Reviews Best Online Brokers Best Life Insurance Companies Best CD Rates Best Savings Accounts Best Personal Loans Best Credit Repair Companies Best Mortgage Rates Best Auto Loan Rates Best Credit Cards View All Academy Investing for Beginners Trading for Beginners Become a Day Trader Technical Analysis All Investing Courses All Trading Courses View All TradeSearchSearchPlease fill out this field.SearchSearchPlease fill out this field.InvestingInvesting Stocks Bonds Fixed Income Mutual Funds ETFs Options 401(k) Roth IRA Fundamental Analysis Technical Analysis Markets View All SimulatorSimulator Login / Portfolio Trade Research My Games Leaderboard EconomyEconomy Government Policy Monetary Policy Fiscal Policy View All Personal FinancePersonal Finance Financial Literacy Retirement Budgeting Saving Taxes Home Ownership View All NewsNews Markets Companies Earnings Economy Crypto Personal Finance Government View All ReviewsReviews Best Online Brokers Best Life Insurance Companies Best CD Rates Best Savings Accounts Best Personal Loans Best Credit Repair Companies Best Mortgage Rates Best Auto Loan Rates Best Credit Cards View All AcademyAcademy Investing for Beginners Trading for Beginners Become a Day Trader Technical Analysis All Investing Courses All Trading Courses View All Financial Terms Newsletter About Us Follow Us Facebook Instagram LinkedIn TikTok Twitter YouTube Table of ContentsExpandTable of Contents3 Forms of Market HypothesesWeak FormSemi-Strong FormStrong FormAnomaliesEfficient Market Hypothesis FAQsTradingTrading StrategiesThe Weak, Strong, and Semi-Strong Efficient Market HypothesesLearn about the three versions of the efficient market hypothesis
The EMH has three forms. The strong form assumes that all past and current information in a market, whether public or private, is accounted for in prices. The semi-strong form assumes that only publicly-available information is incorporated into prices, but privately-held information may not be. The weak form concedes that markets tend to be efficient but anomalies can and do occur, which can be exploited (which tends to remove the anomaly, restoring efficiency via arbitrage). In reality, only the weak form is thought to exist in most markets, if any.
To test the semi-strong version of the EMH, one can see if a stock's price gaps up or down when previously private news is released. For instance, a proposed merger or dismal earnings announcement would be known by insiders but not the public. Therefore, this information is not correctly priced into the shares until it is made available. At that point, the stock may jump or slump, depending on the nature of the news, as investors and traders incorporate this new information.
Summary: Flat interfaces often use weak signifiers. In an eyetracking experiment comparing different kinds of clickability clues, UIs with weak signifiers required more user effort than strong ones.
We took 9 web pages from live websites and modified them to create two nearly identical versions of each page, with the same layout, content and visual style. The two versions differed only in the use of strong, weak, or absent signifiers for interactive elements (buttons, links, tabs, sliders).
In some cases, that meant taking an already flat page and adding shadows, gradients, and text treatments to add depth and increase the strength of the clickability signifiers. In other cases, we took a page that already had strong, traditional signifiers, and we created an ultraflat version. We were careful that the modifications we provided were reasonable and realistic.
Heatmaps are quantitative visualizations that aggregate the number and duration of eye fixations on a stimulus (the UI). They can be created from the gaze data of many participants, as long as they all look at the same stimulus with the same task.
When comparing the two versions of each page pair (strong signifiers vs. weak signifiers) we found that the pages fell into two groups: those with nearly identical user gaze patterns for the two versions, and those with different user gaze patterns (as indicated by the heatmaps).
Of the pages we tested, 6 out of the 9 pairs had different user gaze patterns. With the exception of the signifier strength, we eliminated all other variations in page design within a given pair, so we can conclude that the signifiers changed how users processed the page in their task. 59ce067264
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