IBM developing world's smallest computer

Credit: IBM Research
Most people are familiar with Moore's Law, but few have heard of Bell's Law – a related phenomenon coined by U.S. engineer Gordon Bell. This describes how a new class of computing devices tends to emerge about every decade or so, each 100 times smaller than the last. The shrinking volume of machines becomes obvious when you look back at the history of technology.

The 1960s, for example, were characterised by large mainframes that often filled entire rooms. The 1970s saw the adoption of "minicomputers" that were cheaper and smaller. Personal computing emerged in the early 1980s and laptops became popular in the 1990s. This was followed by mobile phones from the 2000s onwards, which themselves became ever thinner and more compact with each passing year, along with tablets and e-readers. More recently there has been rapid growth in wireless sensor networks that is giving birth to the Internet of Things (IoT).

The new computer announced by IBM is just 1mm x 1mm across, making it the smallest machine of its kind to ever be developed. It will feature as many as a million transistors, a solar cell and communications module. The company predicts these devices will be in widespread use within five years, embedded in all manner of everyday objects. So-called "cryptographic anchors" and blockchain technology will ensure a product's authenticity – from its point of origin to the hands of the customer. These high-tech, miniature watermarks will (for example) verify that products have originated from the factory the distributor claims they are from, and are not counterfeits mixed in with genuine items.

In some countries, nearly 70 percent of certain life-saving pharmaceuticals are counterfeit and the overall cost of fraud to the global economy is more than $600bn every year. This new generation of tiny computers will monitor, analyse, communicate and even act on data.

"These [crypto-anchor] technologies pave the way for new solutions that tackle food safety, authenticity of manufactured components, genetically modified products, identification of counterfeit objects and provenance of luxury goods," says IBM research chief, Arvind Krishna.

Looking further into the future – if Bell's Law continues – devices are likely to be small enough to fit inside blood cells within a few decades. The potential applications then will become like science fiction: could we see a merger between humans and machines?

Source: https://www.futuretimeline.net/
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Computer program learns to replicate human handwriting

Researchers at University College London have devised a software algorithm able to scan and replicate almost anyone's handwriting
In a world increasingly dominated by the QWERTY keyboard, computer scientists at University College London (UCL) have developed software which may spark the comeback of the handwritten word, by analysing the handwriting of any individual and accurately replicating it. The scientists have created "My Text in Your Handwriting" – a programme which semi-automatically examines a sample of a person's handwriting that can be as little as one paragraph, and generates new text saying whatever the user wishes, as if the author had handwritten it themselves. "Our software has lots of valuable applications," says lead author, Dr Tom Haines. "Stroke victims, for example, may be able to formulate letters without the concern of illegibility, or someone sending flowers as a gift could include a handwritten note without even going into the florist. It could also be used in comic books where a piece of handwritten text can be translated into different languages without losing the author's original style." Published in ACM Transactions on Graphics, the machine learning algorithm is built around glyphs – a specific instance of a character. Authors produce different glyphs to represent the same element of writing – the way one individual writes an "a" will usually be different to the way others write an "a". Although an individual's writing has slight variations, every author has a recognisable style that manifests in their glyphs and spacing. The software learns what is consistent across an individual's style and reproduces this.
To generate an individual's handwriting, the software analyses and replicates the author's specific character choices, pen-line texture, colour and the inter-character ligatures (the joining-up between letters), as well as vertical and horizontal spacing. Co-author, Dr Oisin Mac Aodha (UCL Computer Science), said: "Up until now, the only way to produce computer-generated text that resembles a specific person's handwriting would be to use a relevant font. The problem with such fonts is that it is often clear that the text has not been penned by hand, which loses the character and personal touch of a handwritten piece of text. What we've developed removes this problem and so could be used in a wide variety of commercial and personal circumstances." The system is flexible enough that samples from historical documents can be used with little extra effort. Thus far, the scientists have analysed and replicated the handwriting of such figures as Abraham Lincoln, Frida Kahlo and Arthur Conan Doyle. Infamously, Conan Doyle never actually wrote Sherlock Holmes as saying, "Elementary my dear Watson" but the team have produced evidence to make you think otherwise. To test the effectiveness of their software, the research team asked people to distinguish between handwritten envelopes and ones
created by their automatic software.  People were tricked by the computer-generated writing up to 40% of the time. Given how convincing it can be, some may believe this method could help in forging documents – but the team explained it works both ways and could actually help in detecting forgeries. "Forgery and forensic handwriting analysis are still almost entirely manual processes – but by taking the novel approach of viewing handwriting as texture-synthesis, we can use our software to characterise handwriting to quantify the odds that something was forged," explained Dr Gabriel Brostow, senior author. "For example, we could calculate what ratio of people start their 'o's' at the bottom versus the top and this kind of detailed analysis could reduce the forensics service's reliance on heuristics."Computer program learns to replicate human handwriting
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