In the U.S., firearms are one of the few products which are exempt from federal consumer product safety regulations. This exemption derives from the Consumer Product Safety Act of 1972 which explicitly prevents the Consumer Product Safety Commission from regulating firearms and ammunition. As a direct result, there remains no federal agency responsible for ensuring the safety of firearms prior to firearms being sold to consumers. This legislative policy can be disasterous, as with the case of the SIG Sauer P320 pistol, a firearm which is prone to firing without the trigger having been pulled. The SIG Sauer P320 firearm is effectively always engaged within a cocked position, with the weapon ready to fire even when not intended by the end user (e.g. holstered and on the hip of the end user etc.). The SIG Sauer P320 is a striker fired firearm and does not have a manual safety by default. Early versions of the design had issues in which the internal components (e.g. trigger, sear, striker etc.) could inadvertently engage, causing an unintentional discharge. This has resulted in law enforcement and civilians accidentally harming themselves and others with accidental misfires. As of 2016, 80 people have been harmed by this particular firearm. In 2017, the manufacturer SIG Sauer Inc. offered a voluntary upgrade program, not a recall but rather an offer to modify the design of this firearm to improve safety features, including adjustments to the trigger, sear, and striker mechanisms
Recently, many of the improvements made within the artificial intelligence sector have been due to the technology of “deep learning” which is also referred to as an “artificial neural network”. Traditional software is not intuitive as it simply follows a set of instructions predetermined by a programmer. If the software runs into a new problem which it has no answer prewritten for, it crashes. Deep learning is different as software can now write its own instructions instead of reading the instruction(s) of a programmer. Currently, as of 2021, deep learning is the equivalent of an all powerful, dim witted genie as it has the ability to evaluate the pixels of a photograph of a bottle of water, and can recognize with astonishing accuracy photographs of other water bottles, however it has no idea what the concept of water or the water bottle itself is, what the end user does to drink from the water bottle, what the end user needs the water for etc. This differs in human beings however as humans learn from a sample size of one, and are able to surmise the purpose of water and everything else which is relevant from witnessing it being used upon a single occasion
In 1985, the worlds most powerful computer was the Cray-2 which cost $35,000,000 ($35 million), and could not see, hear, or speak with its environment. Today, smartphones process data 10x faster and cost less than $1000.00, with the ability to see, hear, and interact with the end user (e.g Apple’s Siri, Microsoft’s Cortana, Samsung’s Bixby etc.). In 1956, the International Business Machines Corporation’s best hard drive weighed 2000 lbs., was 5 megabytes in size, and cost $3000.00 per month which equates to $28,000 as of 2019 when accounting for inflation. In 2019, most solid state Universal Serial Bus drives possess 200x as much storage at a minimum and cost less than $5.00