Nike and HP Come Together To Print New Shoes
The first thing that comes to mind whenever HP is mentioned is most probably a printer or a computer. Well to add on this, HP has gone forward to add 3D printing to its list of products.
The first thing that comes to mind whenever HP is mentioned is most probably a printer or a computer. Well to add on this, HP has gone forward to add 3D printing to its list of products. Just recently, HP announced the release of two commercial printers that they believe will change everything as we know in the fields of manufacturing and prototyping. Although this is an entirely different field, the technology used in the yet to be released Jet Fusion 3D printers are a huge step to the future’s manufacturing economy by the HP Printers. Actually, just to get a glimpse of how things as we once knew are on the verge of changing, Nike is already in talks to partner with HP to use the printers for their future products.
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One of the major features of the new printers is their open platform built-in software system. This means that the software’s partners can partner with HP to make the process of designing to print much easier, more integrated, and as intuitive as possible with the systems in existence presently. As such, the printers will give its users an easier time to use the software’s they are most comfortable with as opposed to using propriety applications. In addition, the material used to print is an open platform, which makes its users efficient when it comes to using it instead of procuring or waiting for HP to release the materials necessary for use by the printer.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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