A new field of science claims to be able to predict aesthetic traits, intelligence, and even moral character in embryos. Is this the next step in human evolution or something more dangerous? Consider, if you will, the translucent blob in the eye of a microscope: a human blastocyst, the biological specimen that emerges just five days or so after a fateful encounter between egg and sperm. This bundle of cells, about the size of a grain of sand pulled from a powdery white Caribbean beach, contains the coiled potential of a future life: 46 chromosomes, thousands of genes, and roughly six billion base pairs of DNA--an instruction manual to assemble a one-of-a-kind human. Now imagine a laser pulse snipping a hole in the blastocyst's outermost shell so a handful of cells can be suctioned up by a microscopic pipette. This is the moment, thanks to advances in genetic sequencing technology, when it becomes possible to read virtually that entire instruction manual. An emerging field of science seeks to use the analysis pulled from that procedure to predict what kind of a person that embryo might become. Some parents turn to these tests to avoid passing on devastating genetic disorders that run in their families. A much smaller group, driven by dreams of Ivy League diplomas or attractive, well-behaved offspring, are willing to pay tens of thousands of dollars to optimize for intelligence, appearance, and personality. Some of the most eager early boosters of this technology are members of the Silicon Valley elite, including tech billionaires like Elon Musk, Peter Thiel, and Coinbase CEO Brian Armstrong. Embryo selection is less like a build-a-baby workshop and more akin to a store where parents can shop for their future children from several available models--complete with stat cards. But customers of the companies emerging to provide it to the public may not be getting what they're paying for. Genetics experts have been highlighting the potential deficiencies of this testing for years.

Fishing enthusiast Hunter Ham recently captured footage of an alligator on a Texas beach eating a bull redfish. Gators are primarily freshwater creatures. A 21-year-old woman from Georgia recently broke a statewide fishing record, officials say. The Georgia Department of Natural Resources announced the new state record in a press release on June 5. St. Marys resident Lauren E. Harden caught a 33-pound crevalle jack on May 24 while fishing on Cumberland Island.

B nets are differentiable neural networks that learn discrete boolean-valued functions by gradient descent. B nets have two semantically equivalent aspects: a differentiable soft-net, with real weights, and a non-differentiable hard-net, with boolean weights. We train the soft-net by backpropagation and then'harden' the learned weights to yield boolean weights that bind with the hard-net. The result is a learned discrete function. 'Hardening' involves no loss of accuracy, unlike existing approaches to neural network binarization. Preliminary experiments demonstrate that B nets achieve comparable performance on standard machine learning problems yet are compact (due to 1-bit weights) and interpretable (due to the logical nature of the learnt functions). Neural networks are differentiable functions with weights represented by machine floats. Networks are trained by gradient descent in weight-space, where the direction of descent minimises loss. The gradients are efficiently calculated by the backpropagation algorithm (Rumelhart et al., 1986). This overall approach has led to tremendous advances in machine learning.

"We are finally seeing an inflection point in the industry", says Whipsaw CEO and Principal Designer, Dan Harden as he talks about how robots are slowly entering our households. Back at the beginning of the 2000s, the only robots you could find around the house were probably either toys (RC cars, RoboSapiens), or domestic cleaning robots like the vacuum cleaner or the lawn-mower. Today, home service robots are increasingly becoming an emerging trend, creating a unique new opportunity for designers to establish the identity, personality, form, function, and usability factors of these soon-to-emerge home service robots. "It is one of the most exciting design frontiers since the very founding of our profession", Harden tells Yanko Design. The west has been rather slow in adopting robots in domestic settings (something I often attribute to films like Terminator, iRobot, or Transformers, which haven't really made robots look too friendly), while countries in the east like Japan and China (who haven't been inherently exposed to'evil robots') have traditionally been much more accepting robots in their domestic lives.

A major officiating gaffe occurred in the Stanley Cup playoffs when San Jose's Erik Karlsson scored a goal set up by a hand pass. While hockey officials have the toughest job _ they must be able to skate like the players _ they do not get a pass for their mistakes, either. While Saints fans must be feeling picked on as NFL game officials made another error that damaged them in the opener, it must be noted that pro football hardly has a monopoly on officiating problems. Yes, things have gotten murky in that area in the NFL, so much so that pass interference now can be challenged by coaches and reviewed in video replay. Don't underestimate how big a step that was for the league, though when Commissioner Roger Goodell seeks something, he usually gets it.

Utah Jazz head coach Quin Snyder had heavy praise for reigning MVP James Harden ahead of Game 2. Snyder had compared Harden to artificial intelligence on Tuesday and was asked to expand on that before Wednesday night's game. "The way he plays, there's an artistic nature to it… Obviously he's skilled, but I think the way he processes the game… He literally sees the whole court." I think the way he plays, there's an artistic nature to it. The feel that he has for different things on the court. He's able to put the ball on different locations that he wants, to manipulate spacing.

The Pentagon's new artificial-intelligence strategy, released on Tuesday, aims to get AI out of research labs and into the hands of troops and employees across the Defense Department. But truly transforming the Defense Department into an "AI First" institution will require help from tech companies -- and the military to rethink its approach to the massive data streams that AI needs to work. In a conversation with reporters on Tuesday, Dana Deasy, chief information officer of the Defense Department, and Lt. Gen. Jack Shanahan, who runs its new Joint Artificial Intelligence Center, said the JAIC will develop AI tools and programs to assist with everything the Pentagon does. That will eventually include combat operations, although both said the military won't deviate from its core doctrine that dictates how humans are to have authority over autonomous systems. They said near-term projects include efforts to predict forest fires, better spot network anomalies that can indicate cyber attacks, and, most prominently, predictive maintenance.

Robots and AI have been the talk of town in recent years. Many organizations, such as Foxconn, Amazon, and Siemens, have taken to deploying industrial robots in the workforce for very specific tasks, such as product packaging, assembly, supply chain operations, and so on, automating the manual work traditionally done by the human workers. A survey conducted by the International Federation of Robotics forecasted that by 2018, up to 1.3 million robots will be in service worldwide, with China accounting for more than one-third of all installed. In addition to industrial robots, many other technology giants also made headway building personal robot assistants that we will likely welcome into our homes in the near future. However, with more robots working and living among people and taking more responsibilities in the business environment, we ought to ask ourselves – are these robots adequately secured?